Logistic Regression [ESP66]

Detailed information about this course:

Description

Faculty: Prof. Stanley Lemeshow, PhD

The aim of this course is to provide theoretical and practical training for biostatisticians, epidemiologists, medical researchers and professionals of related disciplines in statistical modeling with particular emphasis on logistic regression. The increasingly popular logistic regression model has become the standard method for regression analysis of binary, multinomial and ordinal response data in the health sciences. Students will become familiar with statistical software packages and the analysis of a real data sets.

Objectives

Upon successful completion of the course, students will have the knowledge, comprehension and/or skills to be able to:

• provide a focused introduction to the logistic regression model and its use in modeling the relationship between a categorical outcome variable and a set of covariates.
• provide guidelines for effective model building and interpreting the resulting of a fitted model within the context of the applied problem including determination of scale of continuous covariates.
• provide guidelines for assessing model performance.
• present a comprehensive discussion of the use of logistic regression modeling for multinomial and ordinal response data and matched case-control data.
  

Participant profile

Public health and medical researchers interested in understanding and implementing the analysis of data with nominal scale responses.

Assessment

Attendance