Indiana University-Purdue University Indianapolis (IUPUI) / The research ideas included in this dissertation are motivated by a large sexually trans
mitted infections (STIs) study (IU Phone study), which is also an ecological momentary
assessment (EMA) study implemented by Indiana University from 2008 to 2013. EMA, as a
group of methods used to collect subjects’ up-to-date behaviors and status, can increase the
accuracy of this information by allowing a participant to self-administer a survey or diary
entry, in their own environment, as close to the occurrence of the behavior as possible. IU
Phone study’s high reporting level shows one of the benefits gain from introducing EMA
in STIs study. As a prospective study lasting for 84 days, participants in IU Phone study
undergo STI testing and complete EMA forms with project-furnished cellular telephones
according to the predetermined schedules. At pre-selected eight-hour intervals, participants
respond to a series of questions to identify sexual and non-sexual interactions with specific
partners including partner name, relationship satisfaction and sexual satisfaction with this
partner, time of each coital event and condom use for each event. etc. STIs lab results of all
the participants are collected weekly as well. We are interested in several variables related
to the risk of infection and sexual or non-sexual behaviors, especially the relationship among
the longitudinal processes of those variables. New statistical models and applications are
established to deal with the data with complex dependence and sampling data structures.
The methodologies covers various of statistical aspect like generalized mixed models, mul
tivariate models and autoregressive and cross-lagged model in longitudinal data analysis,
misclassification adjustment in imperfect diagnostic tests, and variable-domain functional regression in functional data analysis. The contribution of our work is we bridge the meth
ods from different areas with EMA data in the IU Phone study and also build up a novel
understanding of the association among all the variables of interest from different perspec
tives based on the characteristic of the data. Besides all the statistical analyses included in
this dissertation, variety of data visualization techniques also provide informative support
in presenting the complex EMA data structure.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/11288 |
| Date | 18 July 2016 |
| Creators | He, Fei |
| Contributors | Harezlak, Jaroslaw, Liu, Ziyue, Monahan, Patrick, Hensel, Devon J. |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
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