PASS,即Power Analysis and Sample Size,主要用于样本量计算或者固定样本量的情况计算把握度(1-β),软件内容包括几乎所有科研模型,包括以下模型,该软件操作简单,适用于对SAS等编程软件不是很精通的人士,界面中还有辅助解释,例如进行临床试验时采用两组随机对照试验,进行非劣效分析,终点为生存率,那么就可以选择Logrank tests for non_inferiority,直接输入α,1-β,HR0危险比,h1标准组危险度,两组的比例,入组时间,总时间(入组+随诊时间),丢失率,后就可以得到所需样本量,并且结果中最有特色的是还给您提供相关的参考文献,写文章时当然可直接引用这个参考文献了:
Proportions
One Proportion
Inequality Tests
Non-Zero Null Tests
Non-Inferiority Tests
Equivalence Tests
Confidence Intervals
Single-Stage Phase II Clinical Trials
Two-Stage Phase II Clinical Trials
Three-Stage Phase II Clinical Trials
Post-Marketing Surveillance
Two Correlated Proportions
Inequality Tests (McNemar Test)
Inequality Tests (Matched Case-Control Design)
Non-Inferiority Tests
Equivalence Tests
Two Independent Proportions
Inequality Tests
Inequality Tests (Repeated Measures Design)
Non-Zero Null Tests
Non-Inferiority Tests
Equivalence Tests
Confidence Intervals
Group-Sequential Tests
Group-Sequential Tests (Simulation)
Non-Zero Null Group-Sequential Tests (Simulation)
Group-Sequential Non-Inferiority Tests (Simulation)
Inequality Tests (Stratified Design – Cochran-Mantel-Haenszel Test)
Two Independent Proportions in a Cluster-Randomized Design
Inequality Tests
Non-Zero Null Tests
Non-Inferiority Tests
Equivalence Tests
Many Proportions (Contingency Tables)
Chi-Square Tests
Two Ordered Categorical Variable Tests
Cochran-Armitage Test for Trend in Proportions
ROC Curves
Inequality Tests for One ROC Curve
Inequality Tests for Two ROC Curves
Sensitivity and Specificity
Sensitivity and Specificity Test for One Group
Sensitivity Test for Two Groups
Tests for Paired Sensitivities
Control Charts
Control Charts for Process Means (Simulation)
Control Charts for Process Variation (Simulation)
Means
One Mean
Inequality Tests
Inequality Tests (Exponential Data)
Inequality Tests (Simulation)
Inequality Tests (Poisson Data)
Non-Zero Null Tests
Non-Inferiority Tests
Confidence Intervals
Confidence Intervals with Tolerance Probability
Two Independent Means
Inequality Tests using Differences (Two-Sample T-Test)
Inequality Tests (Repeated Measures Design)
Inequality Tests (Exponential Data)
Inequality Tests (Poisson Data)
Inequality Tests (Simulation)
Inequality Tests using Ratios
Non-Zero Null Tests using Differences
Non-Inferiority Tests using Differences
Non-Unity Null Tests using Ratios
Non-Inferiority Tests using Ratios
Equivalence Tests using Differences
Equivalence Tests (Simulation)
Equivalence Tests using Ratios
Confidence Intervals for the Difference
Confidence Intervals for the Difference with Tolerance Probability
Group-Sequential Tests
Group-Sequential Tests (Simulation)
Group-Sequential Tests assuming Normality (Simulation)
Group-Sequential Non-Inferiority Tests (Simulation)
Inequality Tests (Cluster-Randomized Design)
Two Correlated (Paired) Means
Inequality Tests
Inequality Tests (Simulation)
Equivalence Tests (Simulation)
Confidence Intervals
Confidence Intervals with Tolerance Probability
Two Independent Means in a 2×2 Cross-Over Design
Inequality Tests using Differences
Inequality Tests using Ratios
Non-Zero Null Tests using Differences
Non-Inferiority Tests using Differences
Non-Unity Null Tests using Ratios
Non-Inferiority Tests using Ratios
Equivalence Tests using Differences
Equivalence Tests using Ratios
Two Independent Means in a Higher-Order Cross-Over Design
Non-Zero Null Tests using Differences
Non-Inferiority Tests using Differences
Non-Unity Null Tests using Ratios
Non-Inferiority Tests using Ratios
Equivalence Tests using Differences
Equivalence Tests using Ratios
Many Means (ANOVA)
One-Way Analysis of Variance
Analysis of Covariance (ANCOVA)
One-Way Analysis of Variance (Simulation)
Fixed Effects Analysis of Variance
Randomized Block Analysis of Variance
Repeated Measures Analysis of Variance
Mixed Models
Mixed Models
Multiple Comparisons
Multiple Comparisons
Pair-Wise Multiple Comparisons (Simulation)
Multiple Comparisons of Treatments vs. a Control (Simulation)
Multiple Contrasts (Simulation)
Williams Test for the Minimum Effective Dose
Multivariate Means
Hotelling's T2
Multivariate Analysis of Variance (MANOVA)
Microarrays
One-Sample or Paired T-Test
Two-Sample T-Test
Standard Deviations
Confidence Intervals for One Standard Deviation using Standard Deviation
Confidence Intervals for One Standard Deviation with Tolerance Probability
Confidence Intervals for One Standard Deviation using Relative Error
Variances
One Variance
Inequality Tests for One Variance
Confidence Intervals for One Variance using Variance
Confidence Intervals for One Variance with Tolerance Probability
Confidence Intervals for One Variance using Relative Error
Two Variances
Inequality Tests for Two Variances
Confidence Intervals for the Ratio of Two Variances using Variances
Confidence Intervals for the Ratio of Two Variances using Relative Error
Normality Tests
Normality Tests (Simulation)
Survival Analysis
Logrank Tests (Freedman)
Logrank Tests (Lachin and Foulkes)
Logrank Tests for Non-Inferiority
Group-Sequential Logrank Tests
Group-Sequential Logrank Tests (Simulation)
Logrank Tests (Lakatos)
Correlations
Inequality Tests for One Correlation
Confidence Intervals for One Correlation
Inequality Tests for Two Correlations
Inequality Tests for Intraclass Correlation
Kappa Test for Agreement Between Two Raters
Inequality Tests for One Coefficient Alpha
Inequality Tests for Two Coefficient Alphas
Regression
Cox Regression
Linear Regression
Confidence Intervals for Linear Regression Slope
Logistic Regression
Multiple Regression
Poisson Regression
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