CIT Training Course #425

#425

JMP Software: Analysis of Attribute Data

Description:

This one-day course teaches you how to analyze data with a single categorical response variable. After completing this course, you should be able to analyze mosaic plots, frequency tables, and odds ratios; conduct a Cochran-Mantel-Haenszel test for stratified data; perform binary, nominal, and ordinal logistic regression; and interpret a correspondence analysis.

Objectives:

This course will cover:

Stratified Data Analysis and Logistic Regression

recognizing the difference between categorical and continuous data analysis
choosing the scale of measurement for the response variable
examining the distributions of categorical variables
analyzing relationships between categorical variables
performing a stratified analysis of categorical variables
explaining a logistic regression model
performing logistic regression
examining logistic regression reports

Ordinal Logistic Regression and Correspondence Analysis
- calculating and distinguishing odds and odds ratios
- fitting ordinal logistic regression models
- understanding cumulative logits
- applying the proportional odds assumption
- interpreting lack of fit tests
- fitting nominal logistic regression models
- understanding generalized logits
- conducting a correspondence analysis

Who should attend:

NIH staff with some statistical training who want to analyze categorical response data using association and logistic regression techniques.

Instructor(s):

Dr. Mark Bailey, SAS Institute

Time Required:

14 hours

Sections Available:

425 -04F

October 27

9:00 - 5:00

Fernwood Building, Lower Level Classroom

Course Listing