Inferences in Log-Rate Models

Herbert C. Heien, Minnesota State University, Mankato
William A. Baumann, Minnesota State University, Mankato

1st Student's Major

Mathematics and Statistics

1st Student's College

Science, Engineering and Technology

Students' Professional Biography

Herbert C. Heien and William A. Baumann are students in the Department of Mathematics and Statistics at Minnesota State University, Mankato.

Mentor's Name

Mezbahur Rahman

Mentor's Email Address

mezbahur.rahman@mnsu.edu

Mentor's Department

Mathematics and Statistics

Mentor's College

Science, Engineering and Technology

Abstract

Log-Rate models are used in analyzing rates of individuals who are exposed to a risk of having a certain characteristic. The explanatory variables could be categorical or in a continuous scale. In finding a Log-Rate Model, parameters are estimated and goodness-of-fit are studied to carefully extract the best model to fit our data. Here we revisit three aspects of Log-Rate Models using the data set give at the end of the paper. The three aspects are parameter estimation, goodness-of-fit of the model, and marginal effect of the factors.

Recommended Citation

Heien, Herbert C. and Baumann, William A. (2003) "Inferences in Log-Rate Models," Journal of Undergraduate Research at Minnesota State University, Mankato: Vol. 3, Article 2.
DOI: https://doi.org/10.56816/2378-6949.1171
Available at: https://cornerstone.lib.mnsu.edu/jur/vol3/iss1/2