分析及样本量计算软件PASS 2020已正式发布
PASS 2020增加了38个新的样本量程序，包括33个更新或改进的程序。新程序包括组序测试，GEE测试，群集和/或分层设计的置信区间，上市后监视，Split-Mouth设计以及多重比例和泊松率。
对于PASS 2020中新的组顺序样本数量程序，NCSS 2020中有相应的组顺序分析和样本大小重新估计程序。
New Procedures in PASS 2020
Group-Sequential Tests（With Futility Boundary Options）
For each of these group-sequential power and sample size procedures, these are corresponding group-sequential analysis and sample-size re-estimation procedures in NCSS 2020.
Group-Sequential Tests（with Futility Boundary Options）
For each of these group-sequential power and sample size procedures, these are corresponding group-sequential analysis and sample-size re-estimation procedures in NCSS 2020.
Group-Sequential Tests for Two Hazard Rates（Simulation）
Group-Sequential Non-Inferiority Tests for Two Hazard Rates（Simulation）
Group-Sequential Superiority bu a Margin Tests for Two Hazard Rates（Simulation）
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Group-Sequential Non-Inferiority Tests for Two Means with Known Variances（Simulation）
Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances （Simulation）
Group-Sequential Non-Inferiorty T-Tests fpr Two Means（Simulation）
Group-Sequential Superiority by a Margin T-Tests for Two Means （Simulation）
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Group-Sequential Non-Inferiority Tests for Two Proportions （Simulation）
Group-Sequential Superiority by a Margin Tests for Two Proportions （Simulation）
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Group-Sequential Tests for one Means with Known Variance （Simulation）
Group-Sequential T-Tests for One Means （Simulation）
GEE Tests
GEE Tests for Two Means in a Stratified Cluster-Randomized Design
GEE Tests for Two Means in a Cluster-Randomized Design
GEE Tests for Multiple Means in a Cluster-Randomized Design
GEE Tests for Multiple Proportions in a Cluster-Randomized Design
GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design
GEE Tests for Two Correlated Proportions with Dropot
Post-Marketing Surveillance for Poisson Rates
Tests for One Poisson Rate with No Background Incidence （Post-Marketing Surveillance）
Tests for One Poisson Rate with Known Bachground Incidence （Post-Marketing Surveillance）
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Tests for Two Poisson Rates with Background Incidence Estimated by the Control （Post-Marketing Surveillance）
Tests for Two Poisson Rates in a Matched Case-Control Design （Post-Marketing Surveillance）
Split-Mouth Design
Tests for Two Means in a Split-Mouth Design
Tests for Two Proportions in a Split-Mouth Design
Confidence Intervals in Cluster and/or Stratified Design
Confidence Intervals for One Proportion in a Stratified Design
Confidence Intervals foe One Proportion in a Cluster-Randomized Design
Confidence Intervals for One Proportiob in a Stratified Cluster-Randomized Design
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Confidence Intervals for One Means in a Stratified Design
Confidence Intervals for One Means in a Cluster-Randomized Design
Confidence Intervals for One Means in a Stratified Cluster-Randomized Design
Other Cluster-Randomized Design Scenarios
Tests for Two Proportions in a Stratified Cluster-Randomized Design（Cochran-Mantel-Haenszel Tests）
Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design with Adjustment for Varying Cluster Sizes
Mixed Models Tests for Two Means in a Cluster-Randomized Design
Other Proportion Tests
Tests for Two Correlated Proportions with Incomplete Observations
Tests for Multiple Proportions in a One-Way Design
Two-Stage Designs for Tests of One Proportion（Simon）
Multiple Poisson Rates
Tests for Multiple Poisson Rates in a One-Way Design
Exponential Hazard Rate
One-Sample Tests for Exponentail Hazard Rate
Ratio of Two Means
Equivalence Tests for the Ratio of Two Means（Normal Data）
Updated and/or Improved Procedures in PASS 2020
Randomization Lists
Randomization Lists
Conditional Power and Sample Size Re-estimation
Conditional Power and Sample Size Reestimation of Logrank Tests
Conditional Power and Sample Size Reestimation of Non-Inferiority Logrank Tests
Conditional Power and Sample Size Reestimation of Superiority by a Margin Logrank Tets
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Conditional Power and Sample Size Reestimation of Tests for the Difference Between Two Proportions
Conditional Power and Sample Size Reestimation or Non-Inferiority Tests for Two Proportions
Conditional Power and Sample Size Reestimation or Superiority by a Margin tests for Two Proportions
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Conditional Power and Sample Size Reestimation of Tests for One Proportion
Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for One Proportion
Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for One Proportion
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Conditional Power and Sample Size Reestimation of Tests for Two Means in 2×2 Cross-Over Design
Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Means in a 2×2 Cross-Over Design
Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Means in a 2×2 Cross-Over Design
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Conditional Power and Sample Size Reestimation of Paired T-Tests
Conditional Power and Sample Size Reestimation od Paired T-Tests for Non-Inferiority
Conditional Power and Sample Size Reestimation of Paired T-Tests for Superiority by a Margin
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Conditional Power and Sample Size Reestimation of Two-Sample T-Tests
Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Non-Inferiority
Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Superiority by a Margin
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Conditional Power and Sample Size Reestimation of One-Sample T-Tests
Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Non-Inferiority
Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Superiority by a Margin
One-Way ANOVA
One-Way Analysis of Variance F-Tests
One-Way Analysis of Variance F-Tests using Effect Size
One-Way Analysis of Variance Contrasts
Simulation of Means Tests
Tests for One Means（Simulation）
Tests for Paired Means（Simulation）
Tests for Two Means（Simulation）
Mann-Whitney U-or Wilcoxon Rank-Sum Tests（Simulation）
Others Tests
Equivalence Tests for the Ratio of Two Means（Log-Normal Data）
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Tests for Two Proportions in a Stratified Design（Cochran-Mantel-Haenszel Tests）
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Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
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Tests for Two Correlated Proportions（McNemar Tests）
Compatibility of PASS 2020
PAS 1010 is fully compatible with windows 10, 8.1、8、7, and Vista SP2, on both 32-bit and 64-bit operating systems.
