Full metadata
Title
A power study of Gffit statistics as somponents of Pearson chi-square
Description
The Pearson and likelihood ratio statistics are commonly used to test goodness-of-fit for models applied to data from a multinomial distribution. When data are from a table formed by cross-classification of a large number of variables, the common statistics may have low power and inaccurate Type I error level due to sparseness in the cells of the table. The GFfit statistic can be used to examine model fit in subtables. It is proposed to assess model fit by using a new version of GFfit statistic based on orthogonal components of Pearson chi-square as a diagnostic to examine the fit on two-way subtables. However, due to variables with a large number of categories and small sample size, even the GFfit statistic may have low power and inaccurate Type I error level due to sparseness in the two-way subtable. In this dissertation, the theoretical power and empirical power of the GFfit statistic are studied. A method based on subsets of orthogonal components for the GFfit statistic on the subtables is developed to improve the performance of the GFfit statistic. Simulation results for power and type I error rate for several different cases along with comparisons to other diagnostics are presented.
Date Created
2017
Contributors
- Zhu, Junfei (Author)
- Reiser, Mark R. (Thesis advisor)
- Stufken, John (Committee member)
- Zheng, Yi (Committee member)
- St Louis, Robert (Committee member)
- Kao, Ming-Hung (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
: illustrations)
Language
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.44100
Statement of Responsibility
by Junfei Zhu
Description Source
Retrieved on March 7, 2017
Level of coding
full
Note
Partial requirement for: Ph.D., Arizona State University, 2017
Note type
thesis
Includes bibliographical references (pages 121-123)
Note type
bibliography
Field of study: Statistics
System Created
- 2017-06-01 01:36:24
System Modified
- 2021-08-26 09:47:01
- 2 years 8 months ago
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