The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics--means, proportions,
totals, etcetera. Using a model-based approach, complex surveys can be used to evaluate the effectiveness of treatments and to identify risk factors for important diseases such as cancer.
Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to design features such as stratification,
multistage sampling and unequal selection probabilities. In this paper, we accommodate these design features in the analysis of highly skewed response variables arising from large complex
surveys. Specifically, we propose a double-transform-both-sides based estimating equations approach to estimate the median regression parameters of the highly skewed response; the
double-transform-both-sides method applies the same transformation twice to both the response and regression function. The usual sandwich variance estimate can be used in our approach,
whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations. Furthermore, the double-transform-both-sides estimator is relatively robust
to the true underlying distribution, and has much smaller mean square error than the least absolute deviations estimator. The method is motivated by an analysis of laboratory data on
urinary iodine concentration from the National Health and Nutrition Examination Survey. / A Dissertation submitted to the Department of Statistics in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2015. / August 10, 2015. / complex survey, double-transform-both-sides regression, median regression, quantile regression / Includes bibliographical references. / Debajyoti Sinha, Professor Co-Directing Dissertation; Stuart R. Lipsitz, Professor Co-Directing Dissertation; Elwood Carlson, University Representative;
Elizabeth Slate, Committee Member; Fred Huffer, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_291289 |
| Contributors | Fraser, Raphael André (authoraut), Sinha, Debajyoti (professor co-directing dissertation), Lipsitz, Stuart (professor co-directing dissertation), Carlson, Elwood, 1950- (university representative), Slate, Elizabeth H. (committee member), Huffer, Fred W. (Fred William) (committee member), Florida State University (degree granting institution), College of Arts and Sciences (degree granting college), Department of Statistics (degree granting department) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource (53 pages), computer, application/pdf |
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