NCSS PASS is one of the leading software tools for the design of medical trials and pharmaceutical or medical research in general. PASS provides the right methods for the power analysis of over 680 different statistical tests, confidence intervals and research scenarios.
Fast import of historical data – even in foreign data formats – and the simple interface help you focusing on the real problem: determining just the right sample size for your study.
Getting the right sample size involves just three steps:
 Choose the right study design from the navigator
 Enter the required parameters (typically: noise/standard deviation, relevant effect)
 Interpretation of results (Power, sample size)
That’s how easy NCSS PASS makes power calculation. All results will be visualized by highlevel scientific graphs. All graphs are highly customizable and will add an additional level of clarity to your reports.
NCSS PASS offers:
 Calculation of sample size and power
 Validated procedures
 Easy to learn, easy to use
 Professional graphics
 Helpful documentation as part of the output
 Easy export to all commonly used text editors
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PASS  Power Analysis & Sample Size Software
PASS has been finetuned for over 20 years, and has become the leading sample size software choice for clinical trial, pharmaceutical, and other medical research. It has also become a mainstay in all other fields where sample size calculation or evaluation is needed. PASS software performs power analysis and calculates sample sizes for over 680 statistical tests.
PASS Overview
PASS is a standalone system
Although it is integrated with NCSS, you do not have to own NCSS to run it. You can use it with any statistical software you want.
PASS is accurate
It has been extensively verified using books and reference articles. Proof of the accuracy of each procedure is included in the extensive documentation.
PASS comes with complete help system documentation
That contains tutorials, examples, annotated output, references, formulas, validation, and complete instructions on each procedure. All procedures are validated with published articles or books.
Choose PASS. It's more comprehensive, easiertouse, accurate, and less expensive than any other sample size program on the market.
Choosing A Procedure 
Enter The Values 
Further Information
 PASS and NCSS Homepage from the producer NCSS
 PASS complete documentation on the producers website
Trial version of the software PASS
The Producer (NCSS) provides a free trial version of the software. The trial version is 7day's long usable without any restrictions in it's features and/or functions. The license key for the trialversion can be upgraded to a full version, after purchasing an appropriate license. So there is no struggle with reinstallation or reregistrations of licenses.
You can access the trial version on the website of the producer, just click on the following link: http://www.ncss.com/download/pass/freetrial/
System Requirements for the Software PASS
Windows®  
Further Requirements 

Operating System  Windows XP, Vista, 7, 8, 10 (32/64Bit) Windows Server 2003, 2008, 2008 R2, 2012, 2012 R2 
Min. CPU  450 MHz or higher 
Min. RAM  256 MB 
Disc Space  120 MB 
Pass on MAC OS X
A Windows emulator (such as Parallels) is required to run PASS on a Mac!
New Features in PASS 16
PASS 16 adds over 55 new sample size procedures.
New Procedures
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)
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 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)
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 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)
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 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)
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 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
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 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)
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 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)
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 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.)
2×2 CrossOver Design – Odds Ratio
 Tests for the Odds Ratio of Two Proportions in a 2×2 CrossOver Design
 NonInferiority Tests for the Odds Ratio of Two Proportions in a 2×2 CrossOver Design
 Superiority by a Margin Tests for the Odds Ratio of Two Proportions in a 2×2 CrossOver Design
 Equivalence Tests for the Odds Ratio of Two Proportions in a 2×2 CrossOver Design
2×2 CrossOver Design – Proportion Difference
 Tests for the Difference of Two Proportions in a 2×2 CrossOver Design
 NonInferiority Tests for the Difference of Two Proportions in a 2×2 CrossOver Design
 Superiority by a Margin Tests for the Difference of Two Proportions in a 2×2 CrossOver Design
 Equivalence Tests for the Difference of Two Proportions in a 2×2 CrossOver Design
2×2 CrossOver Design – Ratio of Poisson Rates
 Tests for the Ratio of Two Poisson Rates in a 2×2 CrossOver Design
 NonInferiority Tests for the Ratio of Two Poisson Rates in a 2×2 CrossOver Design
 Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a 2×2 CrossOver Design
 Equivalence Tests for the Ratio of Two Poisson Rates in a 2×2 CrossOver Design
2×2 CrossOver Design – Generalized Odds Ratio for Ordinal Data
 Tests for the Generalized Odds Ratio for Ordinal Data in a 2×2 CrossOver Design
 NonInferiority Tests for the Generalized Odds Ratio for Ordinal Data in a 2×2 CrossOver Design
 Superiority by a Margin Tests for the Gen. Odds Ratio for Ordinal Data in a 2×2 CrossOver Design
 Equivalence Tests for the Generalized Odds Ratio for Ordinal Data in a 2×2 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 (StuartMaxwell Test)
 Tests for Multiple Correlated Proportions (StuartMaxwell Test)