Peter M. B. Cahusac - Evidence-Based Statistics

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Evidence-Based Statistics: An Introduction to the Evidential Approach – from Likelihood Principle to Statistical Practice The evidential approach is currently underused, despite its mathematical precision and statistical validity. 
 is an accessible and practical text filled with examples, illustrations and exercises. Additionally, the companion website complements and expands on the information contained in the book. 
While the evidential approach is unlikely to replace probability-based methods of statistical inference, it provides a useful addition to any statistician’s “bag of tricks.” In this book: 
It explains how to calculate statistical evidence for commonly used analyses, in a step-by-step fashion Analyses include: t tests, ANOVA (one-way, factorial, between- and within-participants, mixed), categorical analyses (binomial, Poisson, McNemar, rate ratio, odds ratio, data that’s ‘too good to be true’, multi-way tables), correlation, regression and nonparametric analyses (one sample, related samples, independent samples, multiple independent samples, permutation and bootstraps) Equations are given for all analyses, and R statistical code provided for many of the analyses Sample size calculations for evidential probabilities of misleading and weak evidence are explained Useful techniques, like Matthews’s critical prior interval, Goodman’s Bayes factor, and Armitage’s stopping rule are described Recommended for undergraduate and graduate students in any field that relies heavily on statistical analysis, as well as active researchers and professionals in those fields, 
 belongs on the bookshelf of anyone who wants to amplify and empower their approach to statistical analysis.

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8 Appendix CTable C.1 Baseline characteristics of the 104 493 individuals from the Copenh...

List of Illustrations

1 Chapter 1 Figure 1.1 From sampling distribution to likelihood function. The top curve ... Figure 1.2 Effect size versus sample size: which provides most evidence agai... Figure 1.3 A flow diagram illustrating the general procedure of calculating ...

2 Chapter 2 Figure 2.1 The scales for LR and support S . The ‘compressed’ LR scale is app... Figure 2.2 The Greek goddess Themis, personifying justice. She holds the Sca... Figure 2.3 The likelihood function (dark grey) and wider population distribu... Figure 2.4 The likelihood function for the extra sleeping time data. The mea... Figure 2.5 An alternative visualization for the likelihood that produces ide...Figure 2.6 This shows the likelihood function indicating the likelihood if t...Figure 2.7 Calculating the maximum likelihood ratio (LR M). The same likeliho...Figure 2.8 The likelihood function showing likelihood interval limits for S -...Figure 2.9 The support curve for data given in Section 2.1.3. The vertical a...Figure 2.10 (a) Support (log LR) curves for different effect sizes: −0.5, 0....Figure 2.10 (b) The same plot of support curves for effect sizes from −0.5 t...Figure 2.11 Misleading and weak evidence in relation to Type I and Type II e...Figure 2.12 Flowchart showing the steps necessary for the evidential analysi...

3 Chapter 3Figure 3.1 The likelihood function for the difference in sleeping time. The ...Figure 3.2 The likelihood function for the independent samples analysis. Her...Figure 3.3 A Gardner–Altman estimation plot for the independent samples data...Figure 3.4 The likelihood function for the mean difference between Drugs B a...Figure 3.5 Plots of misleading M and weak W probabilities according to sampl...

4 Chapter 4Figure 4.1 Two models for the effects of intensity of training on fitness. (...Figure 4.2 Plot of skill against weeks of practise. The line represents the ...Figure 4.3 Line fitting to linear (a) and quadratic (b) models. In each plot...Figure 4.4 Group means for the factorial ANOVA. The null model is represente...Figure 4.5 Plot of means of hours of extra sleep given three different drugs...

5 Chapter 5Figure 5.1 A plot of the running times in seconds, for 25 competitors in the...Figure 5.2 The likelihood function for the correlation obtained between the ...Figure 5.3 World record running times for women in the 1500 m event. The fir...Figure 5.4 Figure 5.3 with fitted lines added. The dotted line is the quadra...

6 Chapter 6Figure 6.1 The likelihood function for data based on 6 out of 10 patients wh...Figure 6.2 Plot of the support function (log likelihood) for 6 out of 10 dea...Figure 6.3 The quadratic approximation used to generate the support function...Figure 6.4 The quadratic approximation for π = .6 and N = 100, shown as...Figure 6.5 The scaled likelihood function for Poisson parameter μ with ...Figure 6.6 The log likelihood function for the rate ratio, shown as thick da...Figure 6.7 The OR likelihood function for the folic acid and neural tube def...Figure 6.8 The likelihood function for data based on 60 out of 100 patients ...Figure 6.9 The likelihood function for data based on 60 out of 100 patients ...Figure 6.10 Likelihood function for success probability when all 11 newborns...Figure 6.11 The likelihood function for the two studies on ECMO and CMT trea...

7 Chapter 7Figure 7.1 Histogram plot of all the combinations of mean differences betwee...Figure 7.2 The likelihood curve plotted by the R code given at the end of th...Figure 7.3 The likelihood curve plotted by the R code given at the end of th...

8 Chapter 8Figure 8.1 Odds ratios (circular points) and 95% confidence intervals (error...Figure 8.2 The critical prior interval is shown by the rectangular box situa...Figure 8.3 Probability densities of null (continuous curve) and alternative ...Figure 8.4 Plot of the probabilities of the null hypothesis according to spe...Figure 8.5 Similar to Figure 8.4 except using t with 9 df, plot of the proba...Figure 8.6 Using 95% confidence interval or likelihood interval as a stoppin...Figure 8.7 Use of null and counternull. Both vertical lines represent S -2 li...Figure 8.8 Null and counternull values plotted with hours of sleep (left) an...

Guide

1 Cover

2 Table of Contents

3 Begin Reading

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Evidence-Based Statistics

An Introduction to the Evidential Approach — from Likelihood Principle to Statistical Practice

Peter M. B. Cahusac

This edition first published 2021 2021 John Wiley Sons Inc All rights - фото 1

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