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Categorical Data Analysis Using Logistic Regression
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Classroom duration: 3.0 days Live Web duration: 5 half-day sessions Please note the System Requirements below. CEUs: 1.8 | ||
| (This course is not currently scheduled.) |
This course focuses on analyzing categorical response data in scientific fields. The SAS procedures addressed are PROC FREQ, PROC LOGISTIC, and PROC GENMOD. The course is not designed for predictive modelers in business fields.
Learn how to
- recognize when logistic regression is appropriate
- write code in the LOGISTIC procedure for binary, ordinal, and nominal logistic regression
- create effect plots and odds ratio plots using ODS statistical graphics
- create logit plots and use the FREQ procedure for preliminary analyses
- use automatic model building options in PROC LOGISTIC
- assess models for fit and influential observations using PROC LOGISTIC
- create ROC curves for measuring sensitivity and specificity
- perform exact and conditional logistic regression with PROC LOGISTIC
- analyze repeated and clustered data using GEE's in the GENMOD procedure.
Who should attend
Biostatisticians, epidemiologists, social scientists, and physical scientists who analyze categorical response data
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Prerequisites
Before attending this course, you should
- be able to execute SAS programs and create SAS data sets. You can gain this experience by completing the SAS Programming I: Essentials course.
- have experience analyzing frequency tables using SAS software.
- have completed a course in statistics that covers linear regression and logistic regression. You can gain this experience by completing the Statistics I: Introduction to ANOVA, Regression, and Logistic Regression course.
Course Contents
Contingency Table Analysis
- using measures and tests of association
- performing stratified data analysis
- fitting the model
- creating effect plots and odds ratio plots
- using model selection strategies
- assessing the fit of the model
- fitting GEE models
- fitting ordinal logistic regression models
- fitting nominal logistic regression models
- fitting exact logistic regression models
- fitting conditional logistic regression models
Software
This course addresses SAS/STAT, SAS/GRAPH.
Course Materials
Classroom: Students attend classroom courses in one of our public training centers. You receive
a hardcopy of the course notes and, in some courses, can choose to take home a copy of the course data.
Live Web: Students attend Live Web classes using a Web browser and a telephone and interact with their instructor and fellow classmates in real time. Each student receives an e-mail with instructions on how to join the class three business days before the class begins. The instructions e-mail includes a link to download the course materials. Students need to download and print the course materials prior to class.
Live Web: Students attend Live Web classes using a Web browser and a telephone and interact with their instructor and fellow classmates in real time. Each student receives an e-mail with instructions on how to join the class three business days before the class begins. The instructions e-mail includes a link to download the course materials. Students need to download and print the course materials prior to class.
System Requirements
For Live Web, you must
- review and follow the general system requirements.
- complete the course exercises through our virtual lab. The virtual lab allows you to access the software used in class over the Internet, so that you do not need this software on your local machine.
- run this
test to connect to a virtual lab session. If firewall problems prevent you from connecting to the virtual lab, then you will need the following software installed and configured in your environment to participate in the course exercises:
- Base SAS 9.2 or 9.1.3 on a Windows operating system; SAS/STAT software; and SAS/GRAPH software. Please note that a portion of this class covers the new features in SAS 9. Students who are using a release earlier than SAS 9 will not be able to complete approximately 20% of the course exercises.
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If you have suggestions for this course or would like for it to be offered at another
training facility, let us know by adding to our Interest List.
Available for on-site training or can be scheduled at any SAS training facility
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