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Table of Contents
Preface.-I Continuous Outcome Data
Data Spread, Standard Deviations
Data Summaries: Histograms, Wide and Narrow Gaussian Curves
Null-Hypothesis Testing with Graphs
Null-Hypothesis Testing with the T-table
One-Sample Continuous Data (One-Sample T-Test, One-Sample Wilcoxon
Paired Continuous Data (Paired T-Test, Two-Sample Wilcoxon Signed Rank Test)
Unpaired Continuous Data (Unpaired T-Test, Mann-Whitney)
Linear Regression (Regression Coefficients, Correlation Coefficients, and their Standard Errors)
Kendall-Tau Regression for Ordinal Data
Paired Continuous Data, Analysis with Help of Correlation Coefficients
Power Equations
Sample Size Calculations
Confidence Intervals
Equivalence Testing instead of Null-Hypothesis Testing
Noninferiority Testing instead of Null-Hypothesis Testing
Superiority Testing instead of Null-Hypothesis Testing
Missing Data Imputation
Bonferroni Adjustments
Unpaired Analysis of Variance (ANOVA)
Paired Analysis of Variance (ANOVA).-Variability Analysis for One or Two Samples
22 Variability Analysis for Three or More Samples
Confounding
Propensity Score and Propensity Score Matching for Multiple Confounders
Interaction
Accuracy and Reliability Assessments
Robust Tests for Imperfect Data
Non-linear Modeling on a Pocket Calculator
Fuzzy Modeling for Imprecise and Incomplete Data
Bhattacharya Modeling for Unmasking Hidden Gaussian Curves
Item Response Modeling instead of Classical Linear Analysis of Questionnaires
Meta-Analysis
Goodness of Fit Tests for Identifying Nonnormal Data
Non-Parametric Tests for Three or More Samples (Friedman and Kruskal-Wallis)
II Binary Outcome Data.-Data Spread: Standard Deviation, One Sample Z- Test, One Sample Binomial Test
Z-Tests
Phi Tests for Nominal Data
38 Chi-Square Tests
Fisher Exact Tests Convenient for Small Samples
Confounding
Interaction
Chi-square Tests for Large Cross-Tabs
Logarithmic Transformations, a Great Help to Statistical Analyses
Odds Ratios, a Short-Cut for Analyzing Cross-Tabs
Log odds, the Basis of Logistic Regression
Log Likelihood Ratio Tests for the Best Precision
Hierarchical Loglinear Models for Higher Order Cross-Tabs
McNemar Tests for Paired Cross-Tabs
McNemar Odds Ratios
Power Equations
Sample Size Calculations
Accuracy Assessments
Reliability Assessments
Unmasking Fudged Data
Markov Modeling for Predictions outside the Range of Observations
Binary Partitioning with CART (Classification and Regression Tree) Methods
Meta-Analysis
Physicians' Daily Life and the Scientific Method
Incident Analysis and the Scientific Method
Cochran Tests for Large Paired Cross-Tabs.-Index.
Data Spread, Standard Deviations
Data Summaries: Histograms, Wide and Narrow Gaussian Curves
Null-Hypothesis Testing with Graphs
Null-Hypothesis Testing with the T-table
One-Sample Continuous Data (One-Sample T-Test, One-Sample Wilcoxon
Paired Continuous Data (Paired T-Test, Two-Sample Wilcoxon Signed Rank Test)
Unpaired Continuous Data (Unpaired T-Test, Mann-Whitney)
Linear Regression (Regression Coefficients, Correlation Coefficients, and their Standard Errors)
Kendall-Tau Regression for Ordinal Data
Paired Continuous Data, Analysis with Help of Correlation Coefficients
Power Equations
Sample Size Calculations
Confidence Intervals
Equivalence Testing instead of Null-Hypothesis Testing
Noninferiority Testing instead of Null-Hypothesis Testing
Superiority Testing instead of Null-Hypothesis Testing
Missing Data Imputation
Bonferroni Adjustments
Unpaired Analysis of Variance (ANOVA)
Paired Analysis of Variance (ANOVA).-Variability Analysis for One or Two Samples
22 Variability Analysis for Three or More Samples
Confounding
Propensity Score and Propensity Score Matching for Multiple Confounders
Interaction
Accuracy and Reliability Assessments
Robust Tests for Imperfect Data
Non-linear Modeling on a Pocket Calculator
Fuzzy Modeling for Imprecise and Incomplete Data
Bhattacharya Modeling for Unmasking Hidden Gaussian Curves
Item Response Modeling instead of Classical Linear Analysis of Questionnaires
Meta-Analysis
Goodness of Fit Tests for Identifying Nonnormal Data
Non-Parametric Tests for Three or More Samples (Friedman and Kruskal-Wallis)
II Binary Outcome Data.-Data Spread: Standard Deviation, One Sample Z- Test, One Sample Binomial Test
Z-Tests
Phi Tests for Nominal Data
38 Chi-Square Tests
Fisher Exact Tests Convenient for Small Samples
Confounding
Interaction
Chi-square Tests for Large Cross-Tabs
Logarithmic Transformations, a Great Help to Statistical Analyses
Odds Ratios, a Short-Cut for Analyzing Cross-Tabs
Log odds, the Basis of Logistic Regression
Log Likelihood Ratio Tests for the Best Precision
Hierarchical Loglinear Models for Higher Order Cross-Tabs
McNemar Tests for Paired Cross-Tabs
McNemar Odds Ratios
Power Equations
Sample Size Calculations
Accuracy Assessments
Reliability Assessments
Unmasking Fudged Data
Markov Modeling for Predictions outside the Range of Observations
Binary Partitioning with CART (Classification and Regression Tree) Methods
Meta-Analysis
Physicians' Daily Life and the Scientific Method
Incident Analysis and the Scientific Method
Cochran Tests for Large Paired Cross-Tabs.-Index.