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Full-Text Articles in Physical Sciences and Mathematics
Inferences In Log-Rate Models, Herbert C. Heien, William A. Baumann
Inferences In Log-Rate Models, Herbert C. Heien, William A. Baumann
Journal of Undergraduate Research at Minnesota State University, Mankato
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.
Choosing Between Parametric And Non-Parametric Tests, Russ Johnson
Choosing Between Parametric And Non-Parametric Tests, Russ Johnson
Journal of Undergraduate Research at Minnesota State University, Mankato
A common question in comparing two sets of measurements is whether to use a parametric testing procedure or a non-parametric procedure. The question is even more important in dealing with smaller samples. Here, using simulation, several parametric and nonparametric tests, such as, t-test, Normal test, Wilcoxon Rank Sum test, van-der Waerden Score test, and Exponential Score test are compared.