PASS 2023版最新更新

我们很高兴地宣布 PASS 2023 的发布。PASS 2023 增加了 43 个新的样本量程序，并包括各种增强功能。新程序包括大量的多臂治疗与对照程序。还有AUC和Cmax（生物等效性），胜率复合终点，单案例（AB）K设计和戴明回归的新程序。

PASS 2023 中的新程序

Multi-Arm Treatment versus Control

Multi-Arm Tests for Treatment and Control Proportions
Multi-Arm Non-Inferiority Tests for the Difference Between Treatment and Control Proportions
Multi-Arm Superiority by a Margin Tests for the Difference Between Treatment and Control Proportions
Multi-Arm Equivalence Tests for the Difference Between Treatment and Control Proportions
Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Proportions
Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Proportions
Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Proportions
Multi-Arm Non-Inferiority Tests for the Odds Ratio of Treatment and Control Proportions
Multi-Arm Superiority by a Margin Tests for the Odds Ratio of Treatment and Control Proportions
Multi-Arm Equivalence Tests for the Odds Ratio of Treatment and Control Proportions
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Multi-Arm Tests for Treatment and Control Proportions in a Cluster-Randomized Design
Multi-Arm Non-Inferiority Tests for Treatment and Control Proportions in a Cluster-Randomized Design
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Multi-Arm Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
Multi-Arm Non-Inferiority Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
Multi-Arm Superiority by a Margin Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
Multi-Arm Equivalence Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
Multi-Arm Tests for the Ratio of Treatment and Control Means (Normal Data)
Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Means (Normal Data)
Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Means (Normal Data)
Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Means (Normal Data)
Multi-Arm Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
Multi-Arm Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
Multi-Arm Non-Inferiority Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
Multi-Arm Superiority by a Margin Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
Multi-Arm Equivalence Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
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Multi-Arm Tests for Treatment and Control Means in a Cluster-Randomized Design
Multi-Arm Non-Inferiority Tests for Treatment and Control Means in a Cluster-Randomized Design
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Multi-Arm Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
Multi-Arm Non-Inferiority Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
Multi-Arm Superiority by a Margin Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
Multi-Arm Equivalence Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
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Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions
Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions
Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)
Multi-Arm 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 Cross-Over Design (Log-Normal Data)

Win-Ratio Composite Endpoint

Tests for Two Groups using the Win-Ratio Composite Endpoint
Tests for Two Groups using the Win-Ratio Composite Endpoint in a Stratified Design

Single-Case (AB)^K Designs

Tests for the Difference Between Treatment and Control Means in a Balanced Single-Case (AB)^K Design with Multiple Cases

Deming Regression

Deming Regression

改进了 PASS 2023 中的程序

Within-Subject Correlation Input Option

The ρ (Within-Subject Correlation) nuisance parameter input option was added for these procedures.

Non-Inferiority Tests for the Difference Between Two Correlated Proportions
Non-Inferiority 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)
Non-Inferiority Tests for the Difference Between Two Correlated Proportions
Non-Inferiority 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 Tau-b 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 Michaelis-Menten 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 One-Way 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 One-Sample Sensitivity
Confidence Intervals for One-Sample Specificity
Confidence Intervals for One-Sample 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 Cluster-Randomized Design
Confidence Intervals for One Proportion in a Cluster-Randomized Design
Confidence Intervals for One Proportion in a Stratified Cluster-Randomized Design
Confidence Intervals for One Mean in a Stratified Cluster-Randomized Design
Confidence Intervals for the Weibull Shape Parameter
Confidence Intervals for Intraclass Correlation with Assurance Probability (Lower One-Sided)
Confidence Intervals for Intraclass Correlation with Assurance Probability (Two-Sided)
Confidence Intervals for Vaccine Efficacy using a Cohort Design
Confidence Intervals for Vaccine Efficacy using an Unmatched Case-Control Design
Confidence Intervals for the Odds Ratio of Two Proportions using an Unmatched Case-Control 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 Within-Subject Population SD (σᴡ) input options were added.

Paired T-Tests
Paired T-Tests for Non-Inferiority
Paired T-Tests for Superiority by a Margin
Paired T-Tests for Equivalence
Paired Z-Tests
Paired Z-Tests for Non-Inferiority
Paired Z-Tests for Superiority by a Margin
Paired Z-Tests for Equivalence
Paired Wilcoxon Signed-Rank Tests
Paired Wilcoxon Signed-Rank Tests for Non-Inferiority
Paired Wilcoxon Signed-Rank Tests for Superiority by a Margin
Conditional Power and Sample Size Reestimation of Paired T-Tests
Conditional Power and Sample Size Reestimation of Paired T-Tests for Non-Inferiority
Conditional Power and Sample Size Reestimation of Paired T-Tests for Superiority by a Margin
Confidence Intervals for Paired Means
Confidence Intervals for Paired Means with Tolerance Probability
Multiple Testing for One Mean (One-Sample or Paired Data)
Conditional Power and Sample Size Reestimation of Tests for Two Means in a 2x2 Cross-Over Design
Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design
Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design
Tests for Paired Means (Simulation)
Tests for the Difference Between Two Means in a 2x2 Cross-Over Design
Non-Inferiority Tests for the Difference Between Two Means in a 2x2 Cross-Over Design
Superiority by a Margin Tests for the Difference of Two Means in a 2x2 Cross-Over Design
Equivalence Tests for the Difference Between Two Means in a 2x2 Cross-Over Design

摘要声明

简要说明在350多项程序中得到改进。

文档

在数百个章节中对文档进行了改进。

免费试用

单击此处下载 PASS 2023 的免费试用版。

PASS 2023兼容性

PASS 2023在32位和64位操作系统上与Windows 11、10、8.1、8、7和Vista SP2完全兼容。单击此处查看完整的系统要求。

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