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Jin Peng.pdf (483.93 KB)
ETD Abstract Container
Abstract Header
Count Data Models for Injury Data from the National Health Interview Survey (NHIS)
Author Info
Peng, Jin
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=osu1365780835
Abstract Details
Year and Degree
2013, Master of Science, Ohio State University, Biostatistics.
Abstract
Logistic regression has been widely used in analyzing injury data from the National Health Interview Survey (NHIS). However, since its dependent variable is dichotomized to be either “1” (presence of an injury incident) or “0” (absence of an injury incident), logistic regression cannot provide sufficient information for studying the pattern of multiple injury incidents. In this study, several count data models are developed and compared using injury count data from 2006-2011 NHIS. The Zero-Inflated Negative Binomial (ZINB) model turns out to be the optimal count data model for our data. The inferences made from the ZINB regression model are compared with those from the logistic regression model. The results indicate that ZINB model can explore injury proneness and predict the mean number of injuries in the injury-prone population. These goals cannot be achieved by logistic regression although it might fit the dichotomized data well.
Committee
Haikady Nagaraja (Advisor)
Huiyun Xiang (Committee Member)
Pages
72 p.
Subject Headings
Biostatistics
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Citations
Peng, J. (2013).
Count Data Models for Injury Data from the National Health Interview Survey (NHIS)
[Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1365780835
APA Style (7th edition)
Peng, Jin.
Count Data Models for Injury Data from the National Health Interview Survey (NHIS).
2013. Ohio State University, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=osu1365780835.
MLA Style (8th edition)
Peng, Jin. "Count Data Models for Injury Data from the National Health Interview Survey (NHIS)." Master's thesis, Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1365780835
Chicago Manual of Style (17th edition)
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Document number:
osu1365780835
Download Count:
1,107
Copyright Info
© 2013, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.