R section, Spring 2017

R Programming for Categorical Data Analysis

Chapter numbers refer to Agresti, Alan. (2018). An introduction to categorical data analysis. 2nd edition, John Wiley & Sons.


Basics in R Slides


Binomial distribution
Multinomial distribution
Maximum Likelihood estimate
Odds ratio and Relative risk
Hypothesis test and condifence interval Slides


Odds ratio and Relative risk
Pearson chi-squared test
Test of trend for ordinal data Slides


Fisher’s exact test
Cochran Mantel Haenszel statistics
Breslow-Day statistic
Making cross tables Slides


Extended Mantel-Haenszel statistics
Logistic regression Slides


Wald Confidence interval
Profile Likelihood Confidence Interval Slides


Hosmer-Lemeshow test
Plot and Understand Model Specification Slides


Logit Models for Nominal Responses
Plot and Understand Model Specification Slides


Logit Models for Ordinal Responses
Plot and Understand Model Specification
Cohen’s Kappa Statistic Slides


Introduction to meta-analysis
Effect sizes and standard error
Coding reliability
Steps in a meta-analysis
Homogeneity test Slides


More effect sizes and conversions
Fixed effect and random effect models
Multivariate meta-analysis Slides


Textbook for SAS users: Stokes, Maura E., Charles S. Davis, and Gary G. Koch. (2015) Categorical data analysis using SAS. 3rd edition, SAS institute.