Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences
output from statistical software
22 15 Parametric one‐way analysis of variance Introduction One‐Way Analysis of Variance Source of variance; Total, Between-Group, and Within-Group Relationship between the F‐ratio and probability So, what do we do next? Multiple pairwise comparisons; post hoc and a priori analysis Data analysis step 1: one‐way ANOVA Data analysis step 2: Post hoc analysis Example output from statistical software
23 16 Repeated measure analysis of variance Introduction Repeated measures ANOVA Assessing sphericity Mauchly's test Post hoc tests Example output from statistical software
24 17 Complex Analysis of Variance Models Part A: choice of suitable Analysis of Variance models. Using spreadsheets in experimental design Part B: choice of suitable post hoc pairwise comparisons Mixed ANOVA models Bonferroni and alternative correction procedures Holme correction procedure General comments on complex ANOVA models Example output from statistical software
25 18 Non‐parametric ANOVA Overview Limitations of non-parametric ANOVA models Multiple pairwise comparisons following non‐parametric ANOVA Multiple pairwise comparisons using the Mann–Whitney U‐test Multiple pairwise comparisons using the Wilcoxon Signed‐Rank test Multiple pairwise comparisons using a variant of Dunn's test Example output from statistical software
26 19 Correlation analysis Bivariate correlation analysis of parametric data Correlation analysis of non‐parametric data Example output from statistical software
27 20 Regression analysis Linear regression Example output from statistical software
28 21 Chi‐square analysis Assumptions of chi‐square analysis Risk, relative risk, and odds ratio Example output from statistical software Decision Flowchart 3: Inferential Statistics – Tests of Association
29 22 Confidence intervals Overview Statistical significance of confidence intervals
30 23 Permutation test of exact inference Rationale
31 24 General Linear Model The General Linear Model and Descriptive Statistics The General Linear Model and Inferential Statistics
32 Appendix A: Data distribution: probability mass function and probability density functions A.1 Binomial distribution (Chapter 4.iii, Figure 4.4): Probability mass function A.2 Exponential distribution (Chapter 4.v1, Figure 4.5): Probability density function A.3 Normal distribution (Chapter 4.vii, Figure 4.7): Probability density function A.4 Chi‐square distribution (Chapter 4.viii, Figure 4.8): Probability density function A.5 Student t‐distribution (Chapter 4.ix, Figure 4.9): Probability density function A.6 F distribution (Chapter 4.x, Figure 4.10): Probability density function
33 Appendix B: Standard normal probabilities
34 Appendix C: Critical values of the t‐distribution
35 Appendix D: Critical values of the Mann–Whitney U‐statistic