Introduction to Categorical Data Analysis

Categorical data is the data type consisting of categorical variables or of data converted into categories or groups. Categorical data analysis is vital and useful statistical analysis in clinical research since categorical data occupies a large portion of the data we collect and use. This course will start from basis introducing different types of categorical data and characteristics, contingency table, probability distribution, to learn how to calculate and interpret some useful statistic such as odds ratio and relative risk. The last section is about different types of statistical testing for categorical data by cases. Each example will include a hands-on part of using Rstudio to perform the analysis. 

Detailed topics are:

Analyze contingency table 

•Positive/Negative Predictive Value, Sensitivity, Specificity, Type I/II error

•Joint, Marginal, Conditional association

Measure strength of association

•Odds ratio

•Relative Risk

Statistical Testing of independence

•Cases with nominal large sample size data and small sample size data

•Cases with stratified and paired data

•Cases with ordinal data

This course is designed for beginner/intermediate level.