Date of Award
12-2007
Degree Name
Doctor of Philosophy
Department
Statistics
First Advisor
Dr. M. Niewiadomska Bugaj
Second Advisor
Dr. Joshua Naranjo
Third Advisor
Dr. J. C. Wang
Fourth Advisor
Dr. Daniel Frobish
Abstract
We consider two-part models that are mixtures of a point-mass variable with all mass at zero and a continuous random variable. The model may assume a particular distributionh(x) for the continuous part such as a log-normal or a gamma. The response variable is defined as y=(x, d), where d=1 if x > 0 and d=0 if x = 0. The probability distribution function has the following form: fx,d=p 1-d×1-p ×hx d.
Lachenbruch (1976, 2001) proposed several tests to compare means of two populations for this type of data. We proposed a two-part Wald test and a two-part likelihood ratio test to compare &thetas; = (p, m) (p is the proportion of zeros and m is the mean of h(x)), hence the equality of overall means in K independent populations where h( x) is a lognormal distribution. These two test statistics have asymptotically chi-square distribution with 2(k − 1) degrees of freedom. A simulation study was conducted to compare the size and the power of the proposed tests with several other tests (ANOVA, Welch, Brown-Forsythe, and Kruskal-Wallis).
Access Setting
Dissertation-Open Access
Recommended Citation
Daoud, Marwan, "Extensions of Two-Part Tests to Compare K Independent Populations" (2007). Dissertations. 848.
https://scholarworks.wmich.edu/dissertations/848