PASS Upgrade Information
 New in PASS 2024
 New in PASS 2023
 New in PASS 2022
 New in PASS 2021
 New in PASS 2020
 New in PASS 2019
 New in PASS 16
 New in PASS 15
 New in PASS 14
 New in PASS 13
 New in PASS 12
 New in PASS 11
What’s New in PASS 2024?
We are pleased to announce the release of PASS 2024. PASS 2024 adds 40 new sample size procedures and includes a variety of enhancements. Among the new procedures are 16 metaanalysis procedures, 4 procedures for comparing two groups with clustering in only one arm, and 13 additional multiarm treatment versus control procedures. There are also new procedures for specificity, two survival curves using Cox's Proportional Hazards in a clusterrandomized design, and biosimilar tests for two means.
New Procedures in PASS 2024
MetaAnalysis
 MetaAnalysis of Means using a FixedEffects Model
 MetaAnalysis of Means using a RandomEffects Model
 MetaAnalysis of Paired Means using a FixedEffects Model
 MetaAnalysis of Paired Means using a RandomEffects Model
 MetaAnalysis of Means using a FixedEffects Model in a ClusterRandomized Design
 MetaAnalysis of Means using a RandomEffects Model in a ClusterRandomized Design
 
 MetaAnalysis of Correlations using a FixedEffects Model
 MetaAnalysis of Correlations using a RandomEffects Model
 
 MetaAnalysis of Tests for the Odds Ratio of Two Proportions using a FixedEffects Model
 MetaAnalysis of Tests for the Odds Ratio of Two Proportions using a RandomEffects Model
 MetaAnalysis of Tests for the Risk Ratio of Two Proportions using a FixedEffects Model
 MetaAnalysis of Tests for the Risk Ratio of Two Proportions using a RandomEffects Model
 MetaAnalysis of Tests for the Odds Ratio of Two Proportions using a FixedEffects Model in a ClusterRandomized Design
 MetaAnalysis of Tests for the Odds Ratio of Two Proportions using a RandomEffects Model in a ClusterRandomized Design
 MetaAnalysis of Tests for the Risk Ratio of Two Proportions using a FixedEffects Model in a ClusterRandomized Design
 MetaAnalysis of Tests for the Risk Ratio of Two Proportions using a RandomEffects Model in a ClusterRandomized Design
Comparing Two Groups with Clustering in Only One Arm
 Tests for Two Means in a ClusterRandomized Design with Clustering in Only One Arm
 NonInferiority Tests for Two Means in a ClusterRandomized Design with Clustering in Only One Arm
 
 Tests for Two Proportions in a ClusterRandomized Design with Clustering in Only One Arm
 NonInferiority Tests for Two Proportions in a ClusterRandomized Design with Clustering in Only One Arm
MultiArm Treatment versus Control
 MultiArm Equivalence Tests for Treatment and Control Means in a ClusterRandomized Design
 MultiArm Superiority by a Margin Tests for Treatment and Control Means in a ClusterRandomized Design
 
 MultiArm Superiority by a Margin Tests for the Difference of Treatment and Control Proportions in a ClusterRandomized Design
 MultiArm Equivalence Tests for the Difference of Treatment and Control Proportions in a ClusterRandomized Design
 MultiArm Equivalence Tests for the Ratio of Treatment and Control Proportions in a ClusterRandomized Design
 MultiArm NonInferiority Tests for the Ratio of Treatment and Control Proportions in a ClusterRandomized Design
 MultiArm Superiority by a Margin Tests for the Ratio of Treatment and Control Proportions in a ClusterRandomized Design
 
 MultiArm NonInferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions in a ClusterRandomized Design
 MultiArm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions in a ClusterRandomized Design
 
 MultiArm Tests for Survival Curves using Cox's Proportional Hazards in a ClusterRandomized Design
 MultiArm NonInferiority Tests for Survival Curves using Cox's Proportional Hazards in a ClusterRandomized Design
 MultiArm Superiority by a Margin Tests for Survival Curves using Cox's Proportional Hazards in a ClusterRandomized Design
 MultiArm Equivalence Tests for Survival Curves using Cox's Proportional Hazards in a ClusterRandomized Design
Specificity
 Tests for Paired Specificities
 Tests for Two Independent Specificities
Two Survival Curves using Cox's Proportional Hazards in a ClusterRandomized Design
 Tests for Two Survival Curves using Cox's Proportional Hazards in a ClusterRandomized Design
 NonInferiority Tests for Two Survival Curves using Cox's Proportional Hazards in a ClusterRandomized Design
 Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards in a ClusterRandomized Design
 Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards in a ClusterRandomized Design
Biosimilar Tests for Two Means
 Biosimilar Tests for the Difference Between Means using a Parallel, TwoGroup Design
Improved Procedures in PASS 2024
Input and/or Output Updates
The output was enhanced in over 525 procedures. For the procedures below, the input, output, and/or documentation was significantly improved:
 Tests for Paired Sensitivities
 Tests for OneSample Sensitivity and Specificity
 Tests for Two Independent Sensitivities
 
 Tests for Two Means in a ClusterRandomized Design
 NonInferiority Tests for Two Means in a ClusterRandomized Design
 Superiority by a Margin Tests for Two Means in a ClusterRandomized Design
 Equivalence Tests for Two Means in a ClusterRandomized Design
Summary Statements
Summary statements were significantly improved in 188 procedures. Now, all procedure summary statements are customized to the Solve For selection.
Examples
Example output and/or validation examples were improved in 14 procedures.
System Improvements in PASS 2024
Application Scaling (or Zoom)
Application Scaling (Zoom) was added for the ability to customize the size of text throughout PASS. The default application scale is 25% larger, with the option to customize the application scale (zoom) between 100% (the size of PASS 2023 and earlier) and 200%.
Application Data Reset and Restore
Application Data Reset and Restore functionality was added to System Options to make it easier to restore PASS to its factory default settings and restore saved settings.
Free Trial
Click here to download a free trial of PASS 2024.
Compatibility of PASS 2024
PASS 2024 is fully compatible with Windows 11, 10, 8.1, 8, 7, and Vista SP2, on both 32bit and 64bit operating systems. Click here to view the complete system requirements.
Prices
Upgrade from PASS 2023:
$349 (academic/government)
$449 (commercial)
Upgrade from PASS 2022:
$495 (academic/government)
$649 (commercial)
Upgrade from PASS 2021:
$649 (academic/government)
$849 (commercial)
Upgrade from PASS 2020:
$849 (academic/government)
$1049 (commercial)
Upgrade from PASS 2019:
$1049 (academic/government)
$1249 (commercial)
Upgrade from PASS 16:
$1249 (academic/government)
$1449 (commercial)
Upgrade from PASS 15:
$1449 (academic/government)
$1649 (commercial)
Upgrade from PASS 14:
$1649 (academic/government)
$1849 (commercial)
Upgrade from PASS 13*:
$1849 (academic/government)
$2049 (commercial)
*Older versions (e.g., PASS 12, PASS 11, PASS 2008, PASS 2005, PASS 2002, PASS 2000, and PASS 6.0) are not upgradeable. A new license will need to be purchased to obtain PASS 2024.
Click here to view all prices.
Ordering
To order your upgrade, order from our secure online store, email us at sales@ncss.com, call us at 18008986109 (US only) or (801) 5460445, or fax us at (801) 5463907.
Documentation
PDF versions of the documentation are available directly from each procedure window. These may be displayed or printed. The documentation is also available in the help system or online by clicking here.
Procedures added in the PASS 2023 Upgrade from PASS 2022
MultiArm Treatment versus Control
 MultiArm Tests for Treatment and Control Proportions
 MultiArm NonInferiority Tests for the Difference Between Treatment and Control Proportions
 MultiArm Superiority by a Margin Tests for the Difference Between Treatment and Control Proportions
 MultiArm Equivalence Tests for the Difference Between Treatment and Control Proportions
 MultiArm NonInferiority Tests for the Ratio of Treatment and Control Proportions
 MultiArm Superiority by a Margin Tests for the Ratio of Treatment and Control Proportions
 MultiArm Equivalence Tests for the Ratio of Treatment and Control Proportions
 MultiArm NonInferiority Tests for the Odds Ratio of Treatment and Control Proportions
 MultiArm Superiority by a Margin Tests for the Odds Ratio of Treatment and Control Proportions
 MultiArm Equivalence Tests for the Odds Ratio of Treatment and Control Proportions
 
 MultiArm Tests for Treatment and Control Proportions in a ClusterRandomized Design
 MultiArm NonInferiority Tests for Treatment and Control Proportions in a ClusterRandomized Design
 
 MultiArm Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
 MultiArm NonInferiority Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
 MultiArm Superiority by a Margin Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
 MultiArm Equivalence Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
 MultiArm Tests for the Ratio of Treatment and Control Means (Normal Data)
 MultiArm NonInferiority Tests for the Ratio of Treatment and Control Means (Normal Data)
 MultiArm Superiority by a Margin Tests for the Ratio of Treatment and Control Means (Normal Data)
 MultiArm Equivalence Tests for the Ratio of Treatment and Control Means (Normal Data)
 MultiArm Tests for the Ratio of Treatment and Control Means (LogNormal Data)
 MultiArm NonInferiority Tests for the Ratio of Treatment and Control Means (LogNormal Data)
 MultiArm Superiority by a Margin Tests for the Ratio of Treatment and Control Means (LogNormal Data)
 MultiArm Equivalence Tests for the Ratio of Treatment and Control Means (LogNormal Data)
 MultiArm Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
 MultiArm NonInferiority Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
 MultiArm Superiority by a Margin Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
 MultiArm Equivalence Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
 
 MultiArm Tests for Treatment and Control Means in a ClusterRandomized Design
 MultiArm NonInferiority Tests for Treatment and Control Means in a ClusterRandomized Design
 
 MultiArm Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
 MultiArm NonInferiority Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
 MultiArm Superiority by a Margin Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
 MultiArm Equivalence Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
 
 MultiArm NonInferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions
 MultiArm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions
 MultiArm NonInferiority Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)
 MultiArm Superiority by a Margin Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)
AUC and Cmax
 Bioequivalence Tests for AUC and Cmax in a 2x2 CrossOver Design (LogNormal Data)
WinRatio Composite Endpoint
 Tests for Two Groups using the WinRatio Composite Endpoint
 Tests for Two Groups using the WinRatio Composite Endpoint in a Stratified Design
SingleCase (AB)^K Designs
 Tests for the Difference Between Treatment and Control Means in a Balanced SingleCase (AB)^K Design with Multiple Cases
Deming Regression
 Deming Regression
Improved Procedures in PASS 2023
WithinSubject Correlation Input Option
The ρ (WithinSubject Correlation) nuisance parameter input option was added for these procedures.
 NonInferiority Tests for the Difference Between Two Correlated Proportions
 NonInferiority Tests for the Ratio Between Two Correlated Proportions
 Equivalence Tests for the Difference Between Two Correlated Proportions
 Equivalence Tests for the Ratio Between Two Correlated Proportions
Input and/or Output Updates
For these procedures, the input and/or output was improved.
 Tests for Two Correlated Proportions (McNemar Test)
 NonInferiority Tests for the Difference Between Two Correlated Proportions
 NonInferiority Tests for the Ratio Between Two Correlated Proportions
 Equivalence Tests for the Difference Between Two Correlated Proportions
 Equivalence Tests for the Ratio Between Two Correlated Proportions
 Tests for Two Correlated Proportions with Incomplete Observations
 GEE Tests for Two Correlated Proportions with Dropout
 Tests for One Mean (Simulation)
 Confidence Intervals for One Mean with Tolerance Probability
 Confidence Intervals for One Mean
 Confidence Intervals for Paired Means with Tolerance Probability
 Confidence Intervals for Paired Means
 Confidence Intervals for the Difference Between Two Means with Tolerance Probability
 Confidence Intervals for the Difference Between Two Means
 Confidence Intervals for One Standard Deviation using Standard Deviation
 Confidence Intervals for One Standard Deviation using Relative Error
 Confidence Intervals for the Ratio of Two Variances using Variances
 Confidence Intervals for the Ratio of Two Variances using Relative Error
 Confidence Intervals for One Proportion
 Confidence Intervals for One Standard Deviation with Tolerance Probability
 Confidence Intervals for One Variance using Variance
 Confidence Intervals for One Variance using Relative Error
 Confidence Intervals for One Variance with Tolerance Probability
 Confidence Intervals for the Difference Between Two Proportions
 Confidence Intervals for the Ratio of Two Proportions
 Confidence Intervals for the Odds Ratio of Two Proportions
 Confidence Intervals for Linear Regression Slope
 Confidence Intervals for Pearson's Correlation
 Confidence Intervals for Spearman's Rank Correlation
 Confidence Intervals for Kendall's Taub Correlation
 Confidence Intervals for Point Biserial Correlation
 Confidence Intervals for Intraclass Correlation
 Confidence Intervals for Coefficient Alpha
 Confidence Intervals for Kappa
 Confidence Intervals for the Area Under an ROC Curve
 Confidence Intervals for MichaelisMenten Parameters
 Confidence Intervals for Cp
 Confidence Intervals for Cpk
 Confidence Intervals for the Exponential Lifetime Mean
 Confidence Intervals for an Exponential Lifetime Percentile
 Confidence Intervals for Exponential Reliability
 Confidence Intervals for the Exponential Hazard Rate
 Confidence Intervals for OneWay Repeated Measures Contrasts
 Confidence Intervals for the Odds Ratio in Logistic Regression with One Binary X
 Confidence Intervals for the Odds Ratio in Logistic Regression with Two Binary X's
 Confidence Intervals for the Interaction Odds Ratio in Logistic Regression with Two Binary X's
 Confidence Intervals for OneSample Sensitivity
 Confidence Intervals for OneSample Specificity
 Confidence Intervals for OneSample Sensitivity and Specificity
 Confidence Intervals for a Percentile of a Normal Distribution
 Confidence Intervals for One Proportion in a Stratified Design
 Confidence Intervals for One Mean in a Stratified Design
 Confidence Intervals for One Mean in a ClusterRandomized Design
 Confidence Intervals for One Proportion in a ClusterRandomized Design
 Confidence Intervals for One Proportion in a Stratified ClusterRandomized Design
 Confidence Intervals for One Mean in a Stratified ClusterRandomized Design
 Confidence Intervals for the Weibull Shape Parameter
 Confidence Intervals for Intraclass Correlation with Assurance Probability (Lower OneSided)
 Confidence Intervals for Intraclass Correlation with Assurance Probability (TwoSided)
 Confidence Intervals for Vaccine Efficacy using a Cohort Design
 Confidence Intervals for Vaccine Efficacy using an Unmatched CaseControl Design
 Confidence Intervals for the Odds Ratio of Two Proportions using an Unmatched CaseControl Design
 Confidence Intervals for the Difference Between Two Correlated Proportions
Input Options for Paired Variable Standard Deviations
For these procedures, paired variable SD's (σ1 and σ2) and Correlation (ρ) and/or WithinSubject Population SD (σᴡ) input options were added.
 Paired TTests
 Paired TTests for NonInferiority
 Paired TTests for Superiority by a Margin
 Paired TTests for Equivalence
 Paired ZTests
 Paired ZTests for NonInferiority
 Paired ZTests for Superiority by a Margin
 Paired ZTests for Equivalence
 Paired Wilcoxon SignedRank Tests
 Paired Wilcoxon SignedRank Tests for NonInferiority
 Paired Wilcoxon SignedRank Tests for Superiority by a Margin
 Conditional Power and Sample Size Reestimation of Paired TTests
 Conditional Power and Sample Size Reestimation of Paired TTests for NonInferiority
 Conditional Power and Sample Size Reestimation of Paired TTests for Superiority by a Margin
 Confidence Intervals for Paired Means
 Confidence Intervals for Paired Means with Tolerance Probability
 Multiple Testing for One Mean (OneSample or Paired Data)
 Conditional Power and Sample Size Reestimation of Tests for Two Means in a 2x2 CrossOver Design
 Conditional Power and Sample Size Reestimation of NonInferiority Tests for Two Means in a 2x2 CrossOver Design
 Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Means in a 2x2 CrossOver Design
 Tests for Paired Means (Simulation)
 Tests for the Difference Between Two Means in a 2x2 CrossOver Design
 NonInferiority Tests for the Difference Between Two Means in a 2x2 CrossOver Design
 Superiority by a Margin Tests for the Difference of Two Means in a 2x2 CrossOver Design
 Equivalence Tests for the Difference Between Two Means in a 2x2 CrossOver Design
Summary Statements
Summary statements were improved in over 350 procedures.
Documentation
Documentation improvements were made in hundreds of chapters.
Procedures added in the PASS 2022 Upgrade from PASS 2021
Assurance
Assurance is also known as expected power, average power, statistical assurance, hybrid classicalBayesian procedure, or probability of success. For a brief introduction to assurance in PASS, click here.
 Assurance for TwoSample TTests Assuming Equal Variance
 Assurance for TwoSample ZTests Assuming Equal Variance
 Assurance for TwoSample TTests Allowing Unequal Variance
 Assurance for TwoSample TTests for NonInferiority Assuming Equal Variance
 Assurance for TwoSample TTests for Superiority by a Margin Assuming Equal Variance
 Assurance for TwoSample TTests for Equivalence Assuming Equal Variance
 Assurance for TwoSample TTests for NonInferiority Allowing Unequal Variance
 Assurance for TwoSample TTests for Superiority by a Margin Allowing Unequal Variance
 Assurance for TwoSample TTests for Equivalence Allowing Unequal Variance
 
 Assurance for Tests for Two Proportions
 Assurance for NonZero Null Tests for the Difference Between Two Proportions
 Assurance for NonInferiority Tests for the Difference Between Two Proportions
 Assurance for Superiority by a Margin Tests for the Difference Between Two Proportions
 Assurance for Equivalence Tests for the Difference Between Two Proportions
 Assurance for NonUnity Null Tests for the Ratio of Two Proportions
 Assurance for NonUnity Null Tests for the Odds Ratio of Two Proportions
 Assurance for Superiority by a Margin Tests for the Ratio of Two Proportions
 Assurance for NonInferiority Tests for the Ratio of Two Proportions
 Assurance for Superiority by a Margin Tests for the Odds Ratio of Two Proportions
 Assurance for NonInferiority Tests for the Odds Ratio of Two Proportions
 Assurance for Equivalence Tests for the Ratio of Two Proportions
 Assurance for Equivalence Tests for the Odds Ratio of Two Proportions
 
 Assurance for Logrank Tests (Freedman)
 Assurance for Tests for Two Survival Curves Using Cox's Proportional Hazards Model
 Assurance for NonInferiority Tests for Two Survival Curves Using Cox's Proportional Hazards Model
 Assurance for Superiority by a Margin Tests for Two Survival Curves Using Cox's Proportional Hazards Model
 Assurance for Equivalence Tests for Two Survival Curves Using Cox's Proportional Hazards Model
 Assurance for Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
 Assurance for NonInferiority Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
 Assurance for Superiority by a Margin Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
 Assurance for Equivalence Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
 
 Assurance for Tests for the Ratio of Two Negative Binomial Rates
 Assurance for NonInferiority Tests for the Ratio of Two Negative Binomial Rates
 Assurance for Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
 Assurance for Equivalence Tests for the Ratio of Two Negative Binomial Rates
 
 Assurance for Tests for Two Means in a ClusterRandomized Design
 Assurance for NonInferiority Tests for Two Means in a ClusterRandomized Design
 Assurance for Superiority by a Margin Tests for Two Means in a ClusterRandomized Design
 Assurance for Equivalence Tests for Two Means in a ClusterRandomized Design
 Assurance for Tests for Two Proportions in a ClusterRandomized Design
 Assurance for NonZero Null Tests for the Difference of Two Proportions in a ClusterRandomized Design
 Assurance for NonInferiority Tests for the Difference of Two Proportions in a ClusterRandomized Design
 Assurance for Superiority by a Margin Tests for the Difference of Two Proportions in a ClusterRandomized Design
 Assurance for Equivalence Tests for the Difference of Two Proportions in a ClusterRandomized Design
 Assurance for Logrank Tests in a ClusterRandomized Design
 
 Assurance for Tests for the Difference Between Two Poisson Rates
 Assurance for Tests for the Ratio of Two Poisson Rates
 Assurance for NonInferiority Tests for the Ratio of Two Poisson Rates
 Assurance for Superiority by a Margin Tests for the Ratio of Two Poisson Rates
 Assurance for Equivalence Tests for the Ratio of Two Poisson Rates
 
 Assurance for NonInferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
 Assurance for Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions
Bridging Studies
 Bridging Study using the Equivalence Test of Two Groups (Continuous Outcome)
 Bridging Study using a NonInferiority Test of Two Groups (Continuous Outcome)
 
 Bridging Study using the Equivalence Test of Two Groups (Binary Outcome)
 Bridging Study using a NonInferiority Test of Two Groups (Binary Outcome)
 
 Bridging Study Sensitivity Index
 Bridging Study Test of Sensitivity using a TwoGroup TTest (Continuous Outcome)
GroupSequential Tests (with Efficacy & Futility Boundary Options)
For each of these groupsequential power and sample size procedures, there are corresponding groupsequential analysis and samplesize reestimation procedures in NCSS 2022.
 GroupSequential Tests for Two Poisson Rates (Simulation)
 GroupSequential NonInferiority Tests for Two Poisson Rates (Simulation)
 GroupSequential Superiority by a Margin Tests for Two Poisson Rates (Simulation)
 
 GroupSequential Tests for One Hazard Rate (Simulation)
 GroupSequential NonInferiority Tests for One Hazard Rate (Simulation)
 GroupSequential Superiority by a Margin Tests for One Hazard Rate (Simulation)
 
 GroupSequential Tests for One Poisson Rate (Simulation)
 GroupSequential NonInferiority Tests for One Poisson Rate (Simulation)
 GroupSequential Superiority by a Margin Tests for One Poisson Rate (Simulation)
MannWhitney
 MannWhitney U or Wilcoxon RankSum Tests (Noether)
 Stratified WilcoxonMannWhitney (van Elteren) Test
Acceptance Sampling
 Acceptance Sampling for Attributes with Zero Nonconformities
 Acceptance Sampling for Attributes with Fixed Nonconformities
Other
 Tests for the Ratio of Two Poisson Rates (Zhu)
Improved Procedures in PASS 2022
Conditional Power and Sample Size Reestimation
The conditional power procedures for means were improved to include the option of Tk or Zk.
 Conditional Power and Sample Size Reestimation of Tests for Two Means in a 2x2 CrossOver Design
 Conditional Power and Sample Size Reestimation of NonInferiority Tests for Two Means in a 2x2 CrossOver Design
 Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Means in a 2x2 CrossOver Design
 Conditional Power and Sample Size Reestimation of Paired TTests
 Conditional Power and Sample Size Reestimation of Paired TTests for NonInferiority
 Conditional Power and Sample Size Reestimation of Paired TTests for Superiority by a Margin
 Conditional Power and Sample Size Reestimation of TwoSample TTests
 Conditional Power and Sample Size Reestimation of TwoSample TTests for NonInferiority
 Conditional Power and Sample Size Reestimation of TwoSample TTests for Superiority by a Margin
 Conditional Power and Sample Size Reestimation of OneSample TTests
 Conditional Power and Sample Size Reestimation of OneSample TTests for NonInferiority
 Conditional Power and Sample Size Reestimation of OneSample TTests for Superiority by a Margin
Acceptance Sampling
This procedure was improved to allow Lot Size to take on multiple values.
 Acceptance Sampling for Attributes
Difference of Two Proportions
For these procedures, the option to input a proportion and a proportion difference was added.
 NonZero Null Tests for the Difference Between Two Proportions
 NonInferiority Tests for the Difference Between Two Proportions
 Superiority by a Margin Tests for the Difference Between Two Proportions
 Equivalence Tests for the Difference Between Two Proportions
Simple Linear Regression
An RSquared option for variance input was added in these procedures.
 Simple Linear Regression
 NonZero Null Tests for Simple Linear Regression
 NonInferiority Tests for Simple Linear Regression
 Superiority by a Margin Tests for Simple Linear Regression
 Equivalence Tests for Simple Linear Regression
Summary Statements
Summary statements were improved in 85 procedures.
Enhancements in PASS 2022
Windows 11 Compatibility
Testing was performed and the appropriate modifications were completed to make PASS 2022 compatible with Windows 11.
Output Format
The output for all procedures was improved to produce a more readable table format.
Old Output Format
New Output Format
Documentation
All documentation was updated to provide improved readability and consistency.
Old Documentation Appearance
New Documentation Appearance
Procedures added in the PASS 2021 Upgrade from PASS 2020
Vaccine Efficacy
 Confidence Intervals for Vaccine Efficacy using a Cohort Design
 Confidence Intervals for Vaccine Efficacy using an Unmatched CaseControl Design
 
 Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions
 NonInferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
 Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a ClusterRandomized Design
 NonInferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a ClusterRandomized Design
 
 Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
 NonInferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
 Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a ClusterRandomized Design
 NonInferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a ClusterRandomized Design
 
 Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates
 NonInferiority Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates
 
 Superiority by a Margin Tests for Vaccine Efficacy using the Hazard Ratio (Cox's Proportional Hazards Model)
 NonInferiority Tests for Vaccine Efficacy using the Hazard Ratio (Cox's Proportional Hazards Model)
 
 Tests for Vaccine Efficacy with Extremely Low Incidence
 Superiority by a Margin Tests for Vaccine Efficacy with Extremely Low Incidence
 NonInferiority Tests for Vaccine Efficacy with Extremely Low Incidence
 
 Tests for Vaccine Efficacy with Composite Efficacy Measure (Ratio)
 Tests for Vaccine Efficacy with Composite Efficacy Measure (Difference)
GroupSequential Tests (with Efficacy & Futility Boundary Options)
For each of these groupsequential power and sample size procedures, there are corresponding groupsequential analysis and samplesize reestimation procedures in NCSS 2021.
 GroupSequential NonInferiority Tests for One Mean with Known Variance (Simulation)
 GroupSequential Superiority by a Margin Tests for One Mean with Known Variance (Simulation)
 
 GroupSequential NonInferiority TTests for One Mean (Simulation)
 GroupSequential Superiority by a Margin TTests for One Mean (Simulation)
 
 GroupSequential Tests for One Proportion (Simulation)
 GroupSequential NonInferiority Tests for One Proportion (Simulation)
 GroupSequential Superiority by a Margin Tests for One Proportion (Simulation)
Ratio of Two Means
 Tests for the Ratio of Two Means (Normal Data)
 NonInferiority Tests for the Ratio of Two Means (Normal Data)
 Superiority by a Margin Tests for the Ratio of Two Means (Normal Data)
 Equivalence Tests for the Ratio of Two Means in a 2x2 CrossOver Design (Normal Data)
Two Poisson Rates in a ClusterRandomized Design
 Superiority by a Margin Tests for the Difference Between Two Poisson Rates in a ClusterRandomized Design
 NonInferiority Tests for the Difference Between Two Poisson Rates in a ClusterRandomized Design
 
 Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a ClusterRandomized Design
 NonInferiority Tests for the Ratio of Two Poisson Rates in a ClusterRandomized Design
Method Comparison Studies
 Exact Method for Assessing Agreement in Method Comparison Studies
Confidence Intervals
 Confidence Intervals for a Percentile of a Normal Distribution using Assurance Probability
 Confidence Intervals for a Percentile of a Normal Distribution using Expected Width
 
 Confidence Intervals for the BlandAltman Range of Agreement using Assurance Probability
 Confidence Intervals for the BlandAltman Range of Agreement using Expected Width
 
 Confidence Intervals for RegressionBased Reference Limits using Assurance Probability
 Confidence Intervals for RegressionBased Reference Limits using Expected Relative Precision
Studentized Range
 Studentized Range Test
 Studentized Range Tests for Equivalence
 NonZero Null Studentized Range Tests
Analysis of Variance
 OneWay Analysis of Variance Contrasts Allowing Unequal Variances
 OneWay Analysis of Variance Contrasts Assuming Equal Variances
 
 OneWay Analysis of Variance Allowing Unequal Variances
 OneWay Analysis of Variance Assuming Equal Variances (FTests)
 OneWay Analysis of Variance FTests using Effect Size
 
 Equivalence Tests for OneWay Analysis of Variance Assuming Equal Variances
 Equivalence Tests for OneWay Analysis of Variance Allowing Unequal Variances
 NonZero Null Tests for OneWay Analysis of Variance Assuming Equal Variances
 
 2x2 Factorial Analysis of Variance Allowing Unequal Variances
Analysis of Covariance
 Analysis of Covariance (ANCOVA)
 Analysis of Covariance Contrasts
Two Ordered Categorical Variables
 Tests for Two Ordered Categorical Variables (Non Proportional Odds, WilcoxonMannWhitney)
Logrank Tests
 Logrank Tests (Freedman)
Weibull
 OneSample Tests of Weibull Hazard Rates
 Confidence Interval for Weibull Shape Parameter
Fisher's Exact Test
 Fisher's Exact Test
Intraclass Correlation
 Confidence Intervals for Intraclass Correlation with Assurance Probability (Lower OneSided)
 Confidence Intervals for Intraclass Correlation with Assurance Probability (TwoSided)
Two Proportions
 Confidence Intervals for Odds Ratio of Two Proportions using an Unmatched CaseControl Design
 Confidence Intervals for the Difference of Two Correlated Proportions
Phase II Selection Design
 Randomized Phase II Selection Design for Binary Data (Simon)
DoseFinding
 DoseFinding using the Bayesian Continual Reassessment Method (CRM)
Bayesian Approach
 Tests of Two Means Assuming Equal Variances using a Bayesian Approach
ThreeArm Mean Ratio
 Equivalence Tests for the Mean Ratio in a ThreeArm Trial (Normal Data)
Enhancements in PASS 2021
Report Autosizing
A programwide autosizing of report columns was integrated, giving improved column spacing in reports.
Old Report Columns Display
New Report Columns Display
Random Seed
For all procedures that utilize random number generation, a Random Seed option was added, to obtain output reproducibility.
Decimals Display
A systemwide improvement was implemented to better determine the number of decimals to display in each column.
Access Improvements
The Report Options dropdown was added to the Procedure Window toolbar. The menu and toolbar of the Output and Gallery windows were updated.
Window Loading Time
Optimization techniques were employed to improve the loading time of various windows.
Operational Qualification (Validation) Processing Time
The time to execute the operational qualification (allprocedure validation) was significantly reduced.
Procedures added in the PASS 2020 Upgrade from PASS 2019
GroupSequential Tests (with Futility Boundary Options)
For each of these groupsequential power and sample size procedures, there are corresponding groupsequential analysis and samplesize reestimation procedures in NCSS 2020.
 GroupSequential Tests for Two Hazard Rates (Simulation)
 GroupSequential NonInferiority Tests for Two Hazard Rates (Simulation)
 GroupSequential Superiority by a Margin Tests for Two Hazard Rates (Simulation)
 
 GroupSequential NonInferiority Tests for Two Means with Known Variances (Simulation)
 GroupSequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation)
 GroupSequential NonInferiority TTests for Two Means (Simulation)
 GroupSequential Superiority by a Margin TTests for Two Means (Simulation)
 
 GroupSequential NonInferiority Tests for Two Proportions (Simulation)
 GroupSequential Superiority by a Margin Tests for Two Proportions (Simulation)
 
 GroupSequential Tests for One Mean with Known Variance (Simulation)
 GroupSequential TTests for One Mean (Simulation)
GEE Tests
 GEE Tests for Two Means in a Stratified ClusterRandomized Design
 GEE Tests for Two Means in a ClusterRandomized Design
 GEE Tests for Multiple Means in a ClusterRandomized Design
 GEE Tests for Multiple Proportions in a ClusterRandomized Design
 GEE Tests for Multiple Poisson Rates in a ClusterRandomized Design
 GEE Tests for Two Correlated Proportions with Dropout
PostMarketing Surveillance for Poisson Rates
 Tests for One Poisson Rate with No Background Incidence (PostMarketing Surveillance)
 Tests for One Poisson Rate with Known Background Incidence (PostMarketing Surveillance)
 
 Tests for Two Poisson Rates with Background Incidence Estimated by the Control (PostMarketing Surveillance)
 Tests for Two Poisson Rates in a Matched CaseControl Design (PostMarketing Surveillance)
SplitMouth Design
 Tests for Two Means in a SplitMouth Design
 Tests for Two Proportions in a SplitMouth Design
Confidence Intervals in Cluster and/or Stratified Designs
 Confidence Intervals for One Proportion in a Stratified Design
 Confidence Intervals for One Proportion in a ClusterRandomized Design
 Confidence Intervals for One Proportion in a Stratified ClusterRandomized Design
 
 Confidence Intervals for One Mean in a Stratified Design
 Confidence Intervals for One Mean in a ClusterRandomized Design
 Confidence Intervals for One Mean in a Stratified ClusterRandomized Design
Other ClusterRandomized Design Scenarios
 Tests for Two Proportions in a Stratified ClusterRandomized Design (CochranMantelHaenszel Test)
 Tests for the Difference Between Two Poisson Rates in a ClusterRandomized Design with Adjustment for Varying Cluster Sizes
 Mixed Models Tests for Two Means in a ClusterRandomized Design
Other Proportion Tests
 Tests for Two Correlated Proportions with Incomplete Observations
 Tests for Multiple Proportions in a OneWay Design
 TwoStage Designs for Tests of One Proportion (Simon)
Multiple Poisson Rates
 Tests for Multiple Poisson Rates in a OneWay Design
Exponential Hazard Rate
 OneSample Tests for Exponential Hazard Rate
Ratio of Two Means
 Equivalence Tests for the Ratio of Two Means (Normal Data)
Procedures that were Updated and/or Improved in PASS 2020
Randomization Lists
 Randomization Lists
Conditional Power and Sample Size Reestimation
 Conditional Power and Sample Size Reestimation of Logrank Tests
 Conditional Power and Sample Size Reestimation of NonInferiority Logrank Tests
 Conditional Power and Sample Size Reestimation of Superiority by a Margin Logrank Tests
 
 Conditional Power and Sample Size Reestimation of Tests for the Difference Between Two Proportions
 Conditional Power and Sample Size Reestimation of NonInferiority Tests for Two Proportions
 Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Proportions
 
 Conditional Power and Sample Size Reestimation of Tests for One Proportion
 Conditional Power and Sample Size Reestimation of NonInferiority Tests for One Proportion
 Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for One Proportion
 
 Conditional Power and Sample Size Reestimation of Tests for Two Means in a 2x2 CrossOver Design
 Conditional Power and Sample Size Reestimation of NonInferiority Tests for Two Means in a 2x2 CrossOver Design
 Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Means in a 2x2 CrossOver Design
 
 Conditional Power and Sample Size Reestimation of Paired TTests
 Conditional Power and Sample Size Reestimation of Paired TTests for NonInferiority
 Conditional Power and Sample Size Reestimation of Paired TTests for Superiority by a Margin
 
 Conditional Power and Sample Size Reestimation of TwoSample TTests
 Conditional Power and Sample Size Reestimation of TwoSample TTests for NonInferiority
 Conditional Power and Sample Size Reestimation of TwoSample TTests for Superiority by a Margin
 
 Conditional Power and Sample Size Reestimation of OneSample TTests
 Conditional Power and Sample Size Reestimation of OneSample TTests for NonInferiority
 Conditional Power and Sample Size Reestimation of OneSample TTests for Superiority by a Margin
OneWay ANOVA
 OneWay Analysis of Variance FTests
 OneWay Analysis of Variance FTests using Effect Size
 OneWay Analysis of Variance Contrasts
Simulation of Means Tests
 Tests for One Mean (Simulation)
 Tests for Paired Means (Simulation)
 Tests for Two Means (Simulation)
 MannWhitney U or Wilcoxon RankSum Tests (Simulation)
Other Tests
 Equivalence Tests for the Ratio of Two Means (LogNormal Data)
 
 Tests for Two Proportions in a Stratified Design (CochranMantelHaenszel Test)
 
 Tests for the Difference Between Two Poisson Rates in a ClusterRandomized Design
 
 Tests for Two Correlated Proportions (McNemar Test)
Procedures added in the PASS 2019 Upgrade from PASS 16
GroupSequential Tests (with Futility Boundary Options)
For each of these groupsequential power and sample size procedures, there are corresponding groupsequential analysis and samplesize reestimation procedures in NCSS 2019.
 GroupSequential Tests for Two Means with Known Variances (Simulation)
 GroupSequential TTests for Two Means (Simulation)
 GroupSequential Tests for Two Proportions (Simulation)
Conditional Power
 Conditional Power of TwoSample TTests for NonInferiority
 Conditional Power of TwoSample TTests for Superiority by a Margin
 
 Conditional Power of NonInferiority Tests for the Difference Between Two Proportions
 Conditional Power of Superiority by a Margin Tests for the Difference Between Two Proportions
 
 Conditional Power of NonInferiority Logrank Tests
 Conditional Power of Superiority by a Margin Logrank Tests
 
 Conditional Power of NonInferiority Tests for Two Means in a 2x2 CrossOver Design
 Conditional Power of Superiority by a Margin Tests for Two Means in a 2x2 CrossOver Design
 
 Conditional Power of OneSample TTests for NonInferiority
 Conditional Power of OneSample TTests for Superiority by a Margin
 
 Conditional Power of Paired TTests for NonInferiority
 Conditional Power of Paired TTests for Superiority by a Margin
 
 Conditional Power of NonInferiority Tests for One Proportion
 Conditional Power of Superiority by a Margin Tests for One Proportion
Tests of Mediation Effect
 Tests of Mediation Effect using the Sobel Test
 Tests of Mediation Effect in Linear Regression
 Tests of Mediation Effect in Logistic Regression
 Tests of Mediation Effect in Poisson Regression
 Tests of Mediation Effect in Cox Regression
 Joint Tests of Mediation in Linear Regression with Continuous Variables
Two Proportions
 Superiority by a Margin Tests for the Difference Between Two Proportions
 Superiority by a Margin Tests for the Ratio of Two Proportions
 Superiority by a Margin Tests for the Odds Ratio of Two Proportions
 Superiority by a Margin Tests for the Difference of Two Proportions in a ClusterRandomized Design
 Superiority by a Margin Tests for the Ratio of Two Proportions in a ClusterRandomized Design
Mixed Models Tests
 Mixed Models Tests for Two Means at the End of FollowUp in a 3Level Hierarchical Design (Level3 Randomization)
 Mixed Models Tests for Two Means at the End of FollowUp in a 2Level Hierarchical Design
 
 Mixed Models Tests for Interaction in a 2×2 Factorial 2Level Hierarchical Design (Level2 Randomization)
 Mixed Models Tests for Interaction in a 2×2 Factorial 2Level Hierarchical Design (Level1 Randomization)
 
 Mixed Models Tests for Interaction in a 2×2 Factorial 3Level Hierarchical Design (Level3 Randomization)
 Mixed Models Tests for Interaction in a 2×2 Factorial 3Level Hierarchical Design (Level2 Randomization)
 Mixed Models Tests for Interaction in a 2×2 Factorial 3Level Hierarchical Design (Level1 Randomization)
 
 Mixed Models Tests for SlopeInteraction in a 2×2 Factorial 3Level Hierarchical Design with Random Slopes (Level3 Randomization)
 Mixed Models Tests for SlopeInteraction in a 2×2 Factorial 3Level Hierarchical Design with Random Slopes (Level2 Randomization)
 Mixed Models Tests for SlopeInteraction in a 2×2 Factorial 2Level Hierarchical Design with Random Slopes (Level2 Randomization)
 
 Mixed Models Tests for SlopeInteraction in a 2×2 Factorial 3Level Hierarchical Design with Fixed Slopes (Level3 Randomization)
 Mixed Models Tests for SlopeInteraction in a 2×2 Factorial 3Level Hierarchical Design with Fixed Slopes (Level2 Randomization)
 Mixed Models Tests for SlopeInteraction in a 2×2 Factorial 2Level Hierarchical Design with Fixed Slopes (Level2 Randomization)
Simple Linear Regression
 Simple Linear Regression
 NonZero Null Tests for Simple Linear Regression
 NonInferiority Tests for Simple Linear Regression
 Superiority by a Margin Tests for Simple Linear Regression
 Equivalence Tests for Simple Linear Regression
 Simple Linear Regression using RSquared
 NonZero Null Tests for Simple Linear Regression using RSquared
Multiple Regression
 Multiple Regression
Bayesian Adjustment
 Bayesian Adjustment using the Posterior Error Approach
Reference Intervals
 Reference Intervals for Normal Data
 Nonparametric Reference Intervals for NonNormal Data
Pilot Studies
 UCL of the Standard Deviation from a Pilot Study
 Sample Size of a Pilot Study using the Upper Confidence Limit of the SD
 Sample Size of a Pilot Study using the NonCentral t to Allow for Uncertainty in the SD
 Required Sample Size to Detect a Problem in a Pilot Study
 Pilot Study Sample Size Rules of Thumb
Two Groups, TwoPart Model
 Tests for Two Groups Assuming a TwoPart Model
 Tests for Two Groups Assuming a TwoPart Model with Detection Limits
BlandAltman Method
 BlandAltman Method for Assessing Agreement in Method Comparison Studies
WithinSubject Variances
 Equivalence Tests for the Ratio of Two WithinSubject Variances in a Parallel Design
 NonInferiority Tests for the Ratio of Two WithinSubject Variances in a Parallel Design
 Superiority by a Margin Tests for the Ratio of Two WithinSubject Variances in a Parallel Design
 Tests for the Ratio of Two WithinSubject Variances in a Parallel Design
 NonUnity Null Tests for the Ratio of WithinSubject Variances in a Parallel Design
 
 Equivalence Tests for the Ratio of Two WithinSubject Variances in a 2×2M Replicated CrossOver Design
 NonInferiority Tests for the Ratio of Two WithinSubject Variances in a 2×2M Replicated CrossOver Design
 Superiority by a Margin Tests for the Ratio of Two WithinSubject Variances in a 2×2M Replicated CrossOver Design
 Tests for the Ratio of Two WithinSubject Variances in a 2×2M Replicated CrossOver Design
 NonUnity Null Tests for the Ratio of WithinSubject Variances in a 2×2M Replicated CrossOver Design
WithinSubject CV's
 Tests for the Difference of Two WithinSubject CV's in a Parallel Design
 NonZero Null Tests for the Difference of Two WithinSubject CV's in a Parallel Design
 NonInferiority Tests for the Difference of Two WithinSubject CV's in a Parallel Design
 Superiority by a Margin Tests for the Difference of Two WithinSubject CV's in a Parallel Design
 Equivalence Tests for the Difference of Two WithinSubject CV's in a Parallel Design
Variance Ratios
 Tests for the Ratio of Two Variances
 NonUnity Null Tests for the Ratio of Two Variances
 NonInferiority Tests for the Ratio of Two Variances
 Superiority by a Margin Tests for the Ratio of Two Variances
 Equivalence Tests for the Ratio of Two Variances
BetweenSubject Variances
 Tests for Two BetweenSubject Variances in a 2×2M Replicated CrossOver Design
 NonUnity Null Tests for Two BetweenSubject Variances in a 2×2M Replicated CrossOver Design
 NonInferiority Tests for Two BetweenSubject Variances in a 2×2M Replicated CrossOver Design
 Superiority by a Margin Tests for Two BetweenSubject Variances in a 2×2M Replicated CrossOver Design
Two Total Variances
 Tests for Two Total Variances in a 2×2M Replicated CrossOver Design
 NonUnity Null Tests for Two Total Variances in a 2×2M Replicated CrossOver Design
 NonInferiority Tests for Two Total Variances in a 2×2M Replicated CrossOver Design
 Superiority by a Margin Tests for Two Total Variances in a 2×2M Replicated CrossOver Design
 
 Tests for Two Total Variances in a Replicated Design
 NonUnity Null Tests for Two Total Variances in a Replicated Design
 NonInferiority Tests for Two Total Variances in a Replicated Design
 Superiority by a Margin Tests for Two Total Variances in a Replicated Design
 
 Tests for Two Total Variances in a 2×2 CrossOver Design
 NonUnity Null Tests for Two Total Variances in a 2×2 CrossOver Design
 NonInferiority Tests for Two Total Variances in a 2×2 CrossOver Design
 Superiority by a Margin Tests for Two Total Variances in a 2×2 CrossOver Design
Two Between Variances
 Tests for Two Between Variances in a Replicated Design
 NonUnity Null Tests for Two Between Variances in a Replicated Design
 NonInferiority Tests for Two Between Variances in a Replicated Design
 Superiority by a Margin Tests for Two Between Variances in a Replicated Design
One Mean
 OneSample TTests
 OneSample ZTests
 OneSample ZTests for NonInferiority
 OneSample ZTests for Superiority by a Margin
 OneSample ZTests for Equivalence
Wilcoxon SignedRank Tests
 Wilcoxon SignedRank Tests
 Wilcoxon SignedRank Tests for NonInferiority
 Wilcoxon SignedRank Tests for Superiority by a Margin
Paired Tests

 Paired TTests
 Paired TTests for NonInferiority
 Paired TTests for Superiority by a Margin
 
 Paired ZTests
 Paired ZTests for NonInferiority
 Paired ZTests for Superiority by a Margin
 Paired ZTests for Equivalence
 
 Paired Wilcoxon SignedRank Tests
 Paired Wilcoxon SignedRank Tests for NonInferiority
 Paired Wilcoxon SignedRank Tests for Superiority by a Margin
TwoSample TTests
 TwoSample TTests for NonInferiority Assuming Equal Variance
 TwoSample TTests for NonInferiority Allowing Unequal Variance
 
 TwoSample TTests for Superiority by a Margin Assuming Equal Variance
 TwoSample TTests for Superiority by a Margin Allowing Unequal Variance
 
 TwoSample TTests for Equivalence Allowing Unequal Variance
MannWhitney U or Wilcoxon RankSum Tests
 MannWhitney U or Wilcoxon RankSum Tests
 MannWhitney U or Wilcoxon RankSum Tests for NonInferiority
 MannWhitney U or Wilcoxon RankSum Tests for Superiority by a Margin
Updated and/or Improved Procedures in the PASS 2019 Upgrade from PASS 16
Conditional Power
 Conditional Power of Logrank Tests
 Conditional Power of Tests for the Difference Between Two Proportions
 Conditional Power of Tests for One Proportion
 Conditional Power of Tests for Two Means in a 2x2 CrossOver Design
 Conditional Power of Paired TTests
 Conditional Power of TwoSample TTests
 Conditional Power of OneSample TTests
Survival
 Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
 Tests for Two Survival Curves Using Cox's Proportional Hazards Model
 
 NonInferiority Logrank Tests
 NonInferiority Tests for Two Survival Curves Using Cox's Proportional Hazards Model
 NonInferiority Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
 
 Superiority by a Margin Tests for Two Survival Curves Using Cox's Proportional Hazards Model
 Superiority by a Margin Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
 
 Equivalence Tests for Two Survival Curves Using Cox's Proportional Hazards Model
 Equivalence Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
Proportions
 NonInferiority Tests for the Difference Between Two Proportions
 NonInferiority Tests for the Ratio of Two Proportions
 NonInferiority Tests for the Odds Ratio of Two Proportions
 
 NonInferiority Tests for the Difference Between Two Correlated Proportions
 NonInferiority Tests for the Ratio of Two Correlated Proportions
 
 NonInferiority Tests for the Difference of Two Proportions in a ClusterRandomized Design
 NonInferiority Tests for the Ratio of Two Proportions in a ClusterRandomized Design
 
 Equivalence Tests for the Difference Between Two Proportions
 Equivalence Tests for the Ratio of Two Proportions
 Equivalence Tests for the Odds Ratio of Two Proportions
 
 Equivalence Tests for the Difference of Two Proportions in a ClusterRandomized Design
 Equivalence Tests for the Ratio of Two Proportions in a ClusterRandomized Design
 
 Equivalence Tests for the Difference Between Two Correlated Proportions
 Equivalence Tests for the Ratio of Two Correlated Proportions
 
 NonZero Null Tests for the Difference Between Two Proportions
 NonUnity Null Tests for the Ratio of Two Proportions
 NonUnity Null Tests for the Odds Ratio of Two Proportions
 
 NonZero Null Tests for the Difference of Two Proportions in a ClusterRandomized Design
 NonUnity Null Tests for the Ratio of Two Proportions in a ClusterRandomized Design
 
 Tests for Two Proportions in a Stratified Design (CochranMantelHaenszel Test)
 Tests for Two Proportions in a ClusterRandomized Design
Means
 OneSample TTests for Superiority by a Margin
 OneSample TTests for NonInferiority
 OneSample TTests for Equivalence
 
 Paired TTests for Equivalence
 
 TwoSample TTests Assuming Equal Variance
 TwoSample TTests Allowing Unequal Variance
 TwoSample TTests for Equivalence Assuming Equal Variance
 
 Tests for the Ratio of Two Means
 NonInferiority Tests for the Ratio of Two Means
 Superiority by a Margin Tests for the Ratio of Two Means
 Equivalence Tests for the Ratio of Two Means
 
 Tests for the Difference Between Two Means in a 2x2 CrossOver Design
 Tests for the Ratio of Two Means in a 2x2 CrossOver Design
 NonInferiority Tests for the Difference Between Two Means in a 2x2 CrossOver Design
 NonInferiority Tests for the Ratio of Two Means in a 2x2 CrossOver Design
 Superiority by a Margin Tests for the Difference of Two Means in a 2x2 CrossOver Design
 Superiority by a Margin Tests for the Ratio of Two Means in a 2x2 CrossOver Design
 Equivalence Tests for the Difference Between Two Means in a 2x2 CrossOver Design
 Equivalence Tests for the Ratio of Two Means in a 2x2 CrossOver Design
 
 Tests for Two Means in a ClusterRandomized Design
 NonInferiority Tests for Two Means in a ClusterRandomized Design
 Superiority by a Margin Tests for Two Means in a ClusterRandomized Design
 Equivalence Tests for Two Means in a ClusterRandomized Design
 
 Hotelling's OneSample T2
 Hotelling's TwoSample T2
 
 Multiple Testing for One Mean (OneSample or Paired Data)
 Multiple Testing for Two Means
Linear Regression Slope
 Confidence Intervals for Linear Regression Slope
Coefficient Alpha
 Tests for One Coefficient Alpha
 Tests for Two Coefficient Alphas
Variances
 Tests for One Variance
Procedures added in the PASS 16 Upgrade from PASS 15
Logistic Regression
 Tests for the Odds Ratio in Logistic Regression with One Normal X (Wald Test)
 Tests for the Odds Ratio in Logistic Regression with One Normal X and Other Xs (Wald Test)
 Tests for the Odds Ratio in Logistic Regression with One Binary X and Other Xs (Wald Test)
Repeated Measures Slopes (GEE)
 GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Continuous Outcome)
 GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Binary Outcome)
 GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
 
 GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Continuous Outcome)
 GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Count Outcome)
Repeated Measures TimeAveraged Differences (GEE)
 GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Continuous Outcome)
 GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Binary Outcome)
 GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Count Outcome)
 
 GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Continuous Outcome)
 GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Binary Outcome)
 GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Count Outcome)
Hierarchical Design Comparisons using Mixed Models
 Mixed Models Tests for Two Means in a 2Level Hierarchical Design (Level2 Randomization)
 Mixed Models Tests for Two Means in a 2Level Hierarchical Design (Level1 Randomization)
 
 Mixed Models Tests for Two Proportions in a 2Level Hierarchical Design (Level2 Randomization)
 Mixed Models Tests for Two Proportions in a 2Level Hierarchical Design (Level1 Randomization)
 
 Mixed Models Tests for the Slope Difference in a 2Level Hierarchical Design with Fixed Slopes
 Mixed Models Tests for the Slope Difference in a 2Level Hierarchical Design with Random Slopes
 
 Mixed Models Tests for Two Means in a 3Level Hierarchical Design (Level3 Randomization)
 Mixed Models Tests for Two Means in a 3Level Hierarchical Design (Level2 Randomization)
 Mixed Models Tests for Two Means in a 3Level Hierarchical Design (Level1 Randomization)
 
 Mixed Models Tests for Two Proportions in a 3Level Hierarchical Design (Level3 Randomization)
 Mixed Models Tests for Two Proportions in a 3Level Hierarchical Design (Level2 Randomization)
 Mixed Models Tests for Two Proportions in a 3Level Hierarchical Design (Level1 Randomization)
 
 Mixed Models Tests for the Slope Diff. in a 3Level Hier. Design with Fixed Slopes (Level2 Rand.)
 Mixed Models Tests for the Slope Diff. in a 3Level Hier. Design with Random Slopes (Level2 Rand.)
 Mixed Models Tests for the Slope Diff. in a 3Level Hier. Design with Fixed Slopes (Level3 Rand.)
 Mixed Models Tests for the Slope Diff. in a 3Level Hier. Design with Random Slopes (Level3 Rand.)
2x2 CrossOver Design – Odds Ratio
 Tests for the Odds Ratio of Two Proportions in a 2x2 CrossOver Design
 NonInferiority Tests for the Odds Ratio of Two Proportions in a 2x2 CrossOver Design
 Superiority by a Margin Tests for the Odds Ratio of Two Proportions in a 2x2 CrossOver Design
 Equivalence Tests for the Odds Ratio of Two Proportions in a 2x2 CrossOver Design
2x2 CrossOver Design – Proportion Difference
 Tests for the Difference of Two Proportions in a 2x2 CrossOver Design
 NonInferiority Tests for the Difference of Two Proportions in a 2x2 CrossOver Design
 Superiority by a Margin Tests for the Difference of Two Proportions in a 2x2 CrossOver Design
 Equivalence Tests for the Difference of Two Proportions in a 2x2 CrossOver Design
2x2 CrossOver Design – Ratio of Poisson Rates
 Tests for the Ratio of Two Poisson Rates in a 2x2 CrossOver Design
 NonInferiority Tests for the Ratio of Two Poisson Rates in a 2x2 CrossOver Design
 Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a 2x2 CrossOver Design
 Equivalence Tests for the Ratio of Two Poisson Rates in a 2x2 CrossOver Design
2x2 CrossOver Design – Generalized Odds Ratio for Ordinal Data
 Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 CrossOver Design
 NonInferiority Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 CrossOver Design
 Superiority by a Margin Tests for the Gen. Odds Ratio for Ordinal Data in a 2x2 CrossOver Design
 Equivalence Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 CrossOver Design
Williams CrossOver Design – Pairwise Proportion Differences
 Tests for Pairwise Proportion Differences in a Williams CrossOver Design
 NonInferiority Tests for Pairwise Proportion Differences in a Williams CrossOver Design
 Superiority by a Margin Tests for Pairwise Proportion Differences in a Williams CrossOver Design
 Equivalence Tests for Pairwise Proportion Differences in a Williams CrossOver Design
Williams CrossOver Design – Pairwise Mean Differences
 Tests for Pairwise Mean Differences in a Williams CrossOver Design
 NonInferiority Tests for Pairwise Mean Differences in a Williams CrossOver Design
 Superiority by a Margin Tests for Pairwise Mean Differences in a Williams CrossOver Design
 Equivalence Tests for Pairwise Mean Differences in a Williams CrossOver Design
Multiple Correlated Proportions (McNemarBowker Test of Symmetry)
 Tests for Multiple Correlated Proportions (McNemarBowker Test of Symmetry)
Tools and Features added in PASS 16
 Installation Validation Tool for Installation Qualification (IQ)
 Procedure Validation Tool for Operational Qualification (OQ)
 Report Header Formatting and Colors
Installation Validation Tool for Installation Qualification (IQ)
The Installation Validation Tool for Installation Qualification (IQ) may be used to validate that the software is installed completely and correctly. The tool can also be used to verify that no files have been changed since the software was installed.
The Installation Validation Tool compares all PASS installation files against factory requirements and reports if any required files or folders are missing or invalid. Summary and detailed validation reports are created and displayed in the Output Window. If all files and folders pass installation qualification, then you can be certain that the software is installed correctly.
Procedure Validation Tool for Operational Qualification (OQ)
The Procedure Validation Tool for Operational Qualification (OQ) may be used to validate that the software is operating correctly. The tool verifies that one or more (up to all) procedures is/are functioning correctly by loading the procedure(s), executing calculations, and comparing the results to verified and expected outcomes. Summary and detailed validation reports are created and displayed in the Output Window. If all procedures pass operational qualification, then you can be certain that the software is functioning as expected.
Each procedure can also be validated individually by clicking Validate This Procedure in the Help Center or Help menu on any Procedure Window.
Report Header Formatting and Colors
New system options give the user the ability to add (or remove) lines to the titles to improve separation of report sections. Title line color and text color for page headers, titles, and reports may also be specified individually.
Procedures added in the PASS 15 Upgrade from PASS 14
Logistic and Conditional Logistic Regression
 Logistic Regression with One Binary Covariate using the Wald Test
 Logistic Regression with Two Binary Covariates using the Wald Test
 Logistic Regression with Two Binary Covariates and an Interaction using the Wald Test
 Confidence Intervals for the Odds Ratio in a Logistic Regression with Two Binary Covariates
 Confidence Intervals for the Interaction Odds Ratio in a Logistic Regression with Two Binary Covariates
 Tests for the Odds Ratio in a Matched CaseControl Design with a Binary Covariate using Conditional Logistic Regression
 Tests for the Odds Ratio in a Matched CaseControl Design with a Quantitative X using Conditional Logistic Regression
SteppedWedge ClusterRandomized Designs
 Tests for Two Proportions in a SteppedWedge ClusterRandomized Design
 Tests for Two Means in a SteppedWedge ClusterRandomized Design
 Tests for Two Poisson Rates in a SteppedWedge ClusterRandomized Design
Tolerance Intervals
 Tolerance Intervals for Normal Data
 Tolerance Intervals for Any Data (Nonparametric)
 Tolerance Intervals for Exponential Data
 Tolerance Intervals for Gamma Data
Proportions
 GroupSequential Tests for One Proportion in a Fleming Design
 Multiple Comparisons of Proportions vs. Control
 Tests for One Proportion to Demonstrate Conformance with a Reliability Standard
 Tests for One Proportion to Demonstrate Conformance with a Reliability Standard with Fixed Adverse Events
Poisson and Negative Binomial Rates
 NonInferiority Tests for the Ratio of Two Poisson Rates
 NonInferiority Tests for the Ratio of Two Negative Binomial Rates
 Superiority by a Margin Tests for the Ratio of Two Poisson Rates
 Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
 Equivalence Tests for the Ratio of Two Poisson Rates
 Equivalence Tests for the Ratio of Two Negative Binomial Rates
Effect Size
 TwoSample TTests using Effect Size
 Tests for One Mean using Effect Size
 Tests for Paired Means using Effect Size
 Tests for Two Proportions using Effect Size
 Tests for One Proportion using Effect Size
 OneWay Analysis of Variance FTests using Effect Size
 Factorial Analysis of Variance using Effect Size
 Multiple Regression using Effect Size
Survival
 TwoGroup Survival Comparison Tests (Simulation)
Sensitivity and Specificity
 Confidence Intervals for OneSample Sensitivity
 Confidence Intervals for OneSample Specificity
 Confidence Intervals for OneSample Sensitivity and Specificity
MatchedPair Difference in a ClusterRandomized Design
 Tests for the MatchedPair Difference of Two Event Rates in a ClusterRandomized Design
 Tests for the MatchedPair Difference of Two Proportions in a ClusterRandomized Design
 Tests for the MatchedPair Difference of Two Means in a ClusterRandomized Design
Percentiles
 Confidence Intervals for a Percentile of a Normal Distribution
Features added in PASS 15
 Sample Sizes Adjusted for DropOut
 Report of Procedure Input Settings
 Autosave Procedure Settings
Sample Sizes Adjusted for DropOut
The option for a DropoutInflated Sample Size report has been added to most procedures. The user specifies a dropout (lost, not enrolled, etc.) percentage rate, and the report gives the total number of individuals needed such that power requirements will be met after dropouts. That is, the report gives the dropout inflated enrollment sample size.
Report of Procedure Input Settings
An option was added to every procedure to allow the user to show all the procedure input settings as a report of the output.
Autosave Procedure Settings
In PASS 15, the procedure settings are saved for every run of a procedure. This allows the user to go back and load the procedure settings of any PASS 15 run. Each settings file is given a unique datetime stamp to distinguish each run. The autosaved settings file name is also given in the Procedure Input Settings report.
Updated and/or Improved Procedures in PASS 15
Combined Procedures
In previous versions of PASS, some procedures differed only by the input parameter used. In PASS 15, several of these groups of procedures were combined into single procedures.
 Logrank Tests
 GroupSequential Logrank Tests (Simulation)
 TwoSample ZTests Assuming Equal Variance
 TwoSample ZTests Allowing Unequal Variance
 TwoSample TTests Assuming Equal Variance
 TwoSample TTests Allowing Unequal Variance
Repeated Measures
 Repeated Measures Analysis
Regression
 Multiple Regression
Procedures added in the PASS 14 Upgrade from PASS 13
PASS 14 added over 25 new PASS sample size software procedures, including 13 means procedures, 3 rates and counts procedures, 3 survival analysis procedures, 5 regression procedures, and 2 acceptance sampling procedures.
Means
 Equivalence Tests for the Difference Between Two Paired Means
 NonInferiority Tests for Two Means in a ClusterRandomized Design
 Equivalence Tests for Two Means in a ClusterRandomized Design
 Superiority by a Margin Tests for Two Means in a ClusterRandomized Design
 Tests for the Difference of Two Means in a HigherOrder CrossOver Design
 Tests for the Ratio of Two Means in a HigherOrder CrossOver Design
 Tests for Fold Change of Two Means
 MxM CrossOver Designs
 MPeriod CrossOver Designs using Contrasts
 OneWay Repeated Measures
 OneWay Repeated Measures Contrasts
 OneWay Analysis of Variance Contrasts
 Confidence Intervals for OneWay Repeated Measures Contrasts
Rates and Counts
 Tests for the Difference Between Two Poisson Rates
 Tests for the Difference Between Two Poisson Rates in a ClusterRandomized Design
 Tests for the Ratio of Two Negative Binomial Rates
Survival
 Logrank Tests in a ClusterRandomized Design
 OneSample Logrank Tests
 OneSample Cure Model Tests
Regression
 Reference Intervals for Clinical and Lab Medicine
 Tests for the Difference Between Two Linear Regression Slopes
 Tests for the Difference Between Two Linear Regression Intercepts
 Mendelian Randomization with a Binary Outcome
 Mendelian Randomization with a Continuous Outcome
Acceptance Sampling
 Acceptance Sampling for Attributes
 Operating Characteristic Curves for Acceptance Sampling for Attributes
Procedures Updated in the PASS 14 Upgrade from PASS 13
Over 45 procedures were updated and/or improved as well.
Means
 Tests for Two Means using Ratios
 Tests for Two Means in a ClusterRandomized Design
 NonInferiority Tests for the Difference of Two Means in a HigherOrder CrossOver Design
 NonInferiority Tests for the Ratio of Two Means in a HigherOrder CrossOver Design
 Equivalence Tests for the Difference of Two Means in a HigherOrder CrossOver Design
 Equivalence Tests for the Ratio of Two Means in a HigherOrder CrossOver Design
 Superiority by a Margin Tests for the Difference of Two Means in a HigherOrder CrossOver Design
 Superiority by a Margin Tests for the Ratio of Two Means in a HigherOrder CrossOver Design
 OneWay Analysis of Variance FTests
Rates and Counts
 Tests for One Poisson Rate
 Tests for the Ratio of Two Poisson Rates
Proportions
 Tests for One Proportion
 NonInferiority Tests for One Proportion
 Equivalence Tests for One Proportion
 Superiority by a Margin Tests for One Proportion
 Tests for Two Proportions
 Tests for Two Proportions in a Repeated Measures Design
 NonInferiority Tests for the Difference Between Two Proportions
 NonInferiority Tests for the Ratio of Two Proportions
 NonInferiority Tests for the Odds Ratio of Two Proportions
 Equivalence Tests for the Difference Between Two Proportions
 Equivalence Tests for the Ratio of Two Proportions
 Equivalence Tests for the Odds Ratio of Two Proportions
 Superiority by a Margin Tests for the Difference Between Two Proportions
 Superiority by a Margin Tests for the Ratio of Two Proportions
 Superiority by a Margin Tests for the Odds Ratio of Two Proportions
 Confidence Intervals for the Difference Between Two Proportions
 Confidence Intervals for the Ratio of Two Proportions
 Confidence Intervals for the Odds Ratio of Two Proportions
 Tests for Two Correlated Proportions (McNemar Test)
 NonInferiority Tests for the Difference Between Two Correlated Proportions
 NonInferiority Tests for the Ratio of Two Correlated Proportions
 Equivalence Tests for the Difference Between Two Correlated Proportions
 Equivalence Tests for the Ratio of Two Correlated Proportions
 Tests for Two Proportions in a ClusterRandomized Design
 NonInferiority Tests for the Difference of Two Proportions in a ClusterRandomized Design
 NonInferiority Tests for the Ratio of Two Proportions in a ClusterRandomized Design
 Equivalence Tests for the Difference of Two Proportions in a ClusterRandomized Design
 Equivalence Tests for the Ratio of Two Proportions in a ClusterRandomized Design
 Superiority by a Margin Tests for the Difference of Two Proportions in a ClusterRandomized Design
 Superiority by a Margin Tests for the Ratio of Two Proportions in a ClusterRandomized Design
 GroupSequential Tests for Two Proportions (Simulation)
 GroupSequential NonInferiority Tests for the Difference of Two Proportions (Simulation)
 GroupSequential NonInferiority Tests for the Ratio of Two Proportions (Simulation)
 GroupSequential NonInferiority Tests for the Odds Ratio of Two Proportions (Simulation)
 GroupSequential Superiority by a Margin Tests for the Difference of Two Proportions (Simulation)
 GroupSequential Superiority by a Margin Tests for the Ratio of Two Proportions (Simulation)
 GroupSequential Superiority by a Margin Tests for the Odds Ratio of Two Proportions (Simulation)
Features added in the PASS 13 Upgrade from PASS 12
 3D Power and Sample Size Plots
 Multiple Value Selection Improvements
 Help Center and Video Help Expansion
 TwoSample Sample Size Group Allocation Enhancements
3D Power and Sample Size Plots
Multiple Value Selection Improvements
Help Center and Video Help Expansion
Procedures added in the PASS 13 Upgrade from PASS 12
PASS 13 added over 25 new power and sample size procedures, including oneway tests (3), variance tests (5), correlation tests (5), correlation confidence intervals (4), exponential distribution parameter confidence intervals (4), quality control (2), Coefficient (Cronbach's) Alpha confidence interval (1), Kappa confidence interval (1), area under an ROC curve confidence interval (1), MichaelisMenten parameters confidence intervals (1), and tests for two means in a multicenter randomized design (1).
Oneway Tests of Mean or Center
 KruskalWallis Tests (Simulation)
 TerryHoeffding NormalScores Tests of Means (Simulation)
 Van der Waerden Normal Quantiles Tests of Means (Simulation)
Variance Tests
 Bartlett Test of Variances (Simulation)
 Levene Test of Variances (Simulation)
 BrownForsythe Test of Variances (Simulation)
 Conover Test of Variances (Simulation)
 Power Comparison of Tests of Variances (Simulation)
Correlation Tests
 Pearson's Correlation Tests (Simulation)
 Spearman's Rank Correlation Tests (Simulation)
 Kendall's Taub Correlation Tests (Simulation)
 Point Biserial Correlation Tests
 Power Comparison of Correlation Tests (Simulation)
Correlation Confidence Intervals
 Confidence Intervals for Spearman's Rank Correlation
 Confidence Intervals for Kendall's Taub Correlation
 Confidence Intervals for Point Biserial Correlation
 Confidence Intervals for Intraclass Correlation
Exponential Distribution Parameter Confidence Intervals
 Confidence Intervals for the Exponential Lifetime Mean
 Confidence Intervals for an Exponential Lifetime Percentile
 Confidence Intervals for Exponential Reliability
 Confidence Intervals for the Exponential Hazard Rate
Quality Control
 Confidence Intervals for Cp
 Confidence Intervals for Cpk
Other
 Tests for Two Means in a Multicenter Randomized Design
 Confidence Intervals for MichaelisMenten Parameters
 Confidence Intervals for the Area Under an ROC Curve
 Confidence Intervals for Kappa
 Confidence Intervals for Coefficient Alpha
Procedures added in the PASS 12 Upgrade from PASS 11
PASS 12 added over 15 new power and sample size procedures, including z tests (3), conditional power (6), repeated measures (2), noninferiority logrank (2), equivalence logrank (2), Lin's concordance coefficient (1), probit analysis (1), and competing risks (1).
Conditional Power
 Conditional Power of OneSample TTests
 Conditional Power of TwoSample TTests
 Conditional Power of Paired TTests
 Conditional Power of 2x2 CrossOver Designs
 Conditional Power of Logrank Tests
 Conditional Power of OneProportions Tests
 Conditional Power of TwoProportions Tests
ZTest
 TwoSample ZTest Assuming Equal Variances
 TwoSample ZTest Allowing Unequal Variances
Survival Analysis
 Test for Two Survival Curves using Cox Regression
 NonInferiority Test for Two Survival Curves using Cox Regression
 Equivalence Test for Two Survival Curves using Cox Regression
 Superiority Test for Two Survival Curves using Cox Regression
 Test for Difference of Two Hazard Rates Assuming an Exponential Model
 NonInferiority Test for Difference of Two Hazard Rates Assuming an Exponential Model
 Equivalence Test for Difference of Two Hazard Rates Assuming an Exponential Model
 Superiority Test for Comparing Hazard Rates assuming Exponential Data
 Logrank Test Accounting for Competing Risks
Other
 Lin's Concordance Correlation Coefficient
 Probit Analysis
 Test for Comparing Mean Change Score in PrePost Design
 Confidence Interval for a Proportion from a Finite Population
Revised and Simplified
 Repeated Measures Analysis
 MANOVA
 TwoSample TTest Assuming Equal Variances
 TwoSample TTest with Unequal Variances
 MannWhitneyWilcoxon Test
Procedures added in the PASS 11 Upgrade from PASS 2008
PASS 11 added 17 new power and sample size procedures and features to PASS, including procedures for analysis of covariance, groupsequential testing, sensitivity and specificity, Poisson means testing, tests for two ordered categorical variables, Williams test for the minimum effective dose, Control Charts, an enhanced user interface, increased computation speed, and an improved graphics system.
New Procedures in the PASS 11 Upgrade from PASS 2008
 Analysis of Covariance (ANCOVA)
 GroupSequential Tests for Two Means using Simulation
 GroupSequential NonInferiority Tests for Two Means using Simulation
 GroupSequential Tests for Two Proportions using Simulation
 GroupSequential NonInferiority Tests for Two Proportions using Simulation
 GroupSequential Logrank Tests using Simulation
 Sensitivity and Specificity Tests for One Group
 Tests for Independent Sensitivities of Two Groups
 Tests for Paired Sensitivities
 Tests for One Poisson Mean
 Tests for Two Poisson Means
 Tests for Two Ordered Categorical Variables
 Williams Test for the Minimum Effective Dose
 Control Charts for Process Means
 Control Charts for Process Variation
"PASS 13 is fantastic! Better than my new dishwasher and microwave combined."
"I really love this version of NCSS and as teacher and researcher in a medical field I can say there aren't many things I miss in it... The help system is another strong feature; the transformations interface is one of my favorites as well."