Clinical Data Analysis on a Pocket Calculator: Understanding the Scientific Methods of Statistical Reasoning and Hypothesis Testing - Couverture souple
Synopsis
Preface
I Continuous Outcome Data
1 Data Spread, Standard Deviations
2 Data Summaries: Histograms, Wide and Narrow Gaussian Curves
3 Null-Hypothesis Testing with Graphs
4 Null-Hypothesis Testing with the T-table
5 One-Sample Continuous Data (One-Sample T-Test, One-Sample Wilcoxon
6 Paired Continuous Data (Paired T-Test, Two-Sample Wilcoxon Signed Rank Test)
7 Unpaired Continuous Data (Unpaired T-Test, Mann-Whitney)8 Linear Regression (Regression Coefficients, Correlation Coefficients, and their Standard Errors)
9 Kendall-Tau Regression for Ordinal Data
10 Paired Continuous Data, Analysis with Help of Correlation Coefficients
11 Power Equations
12 Sample Size Calculations
13 Confidence Intervals14 Equivalence Testing instead of Null-Hypothesis Testing
15 Noninferiority Testing instead of Null-Hypothesis Testing
16 Superiority Testing instead of Null-Hypothesis Testing
17 Missing Data Imputation
18 Bonferroni Adjustments
19 Unpaired Analysis of Variance (ANOVA)20 Paired Analysis of Variance (ANOVA)
21 Variability Analysis for One or Two Samples
22 Variability Analysis for Three or More Samples
23 Confounding
24 Propensity Score and Propensity Score Matching for Multiple Confounders
25 Interaction
26 Accuracy and Reliability Assessments27 Robust Tests for Imperfect Data
28 Non-linear Modeling on a Pocket Calculator
29 Fuzzy Modeling for Imprecise and Incomplete Data
30 Bhattacharya Modeling for Unmasking Hidden Gaussian Curves
31 Item Response Modeling instead of Classical Linear Analysis of Questionnaires
32 Meta-Analysis 133 Goodness of Fit Tests for Identifying Nonnormal Data
34 Non-Parametric Tests for Three or More Samples (F
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