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133rd Annual Meeting & Exposition December 10-14, 2005 Philadelphia, PA |
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5079.0: Wednesday, December 14, 2005: 8:30 AM-10:00 AM | |||
Oral | |||
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Dimensionality reduction techniques are critical to the analysis of many data sets that contain information on a large number of outcomes. In this session, factor analyses and related methods are proposed, described and evaluated. | |||
Learning Objectives: At the conclusion of the session, the participant in this session will be able to: 1. Articulate how a k-fold likelihood cross-validation can be used to evaluate factor analysis models 2. Apply differential item functioning techniques on scales and instruments used in health outcomes research. 3. Describe the advantages of a path model for investigating the influence of rural residence on health status 4. Describe and distinguish between the various types of multiple indicator problems that complicate the evaluation of large-scale program initiatives. | |||
Marcia A. Testa, MPH, PhD | |||
Evaluating factor analysis models George J. Knafl, PhD, Margaret Grey, DrPH | |||
Assessment of Differential Item Functioning in the HIV Symptom Distress Index Linda G. Marc, ScD, MPH, MS, Lisa F. Berkman, PhD, Charles Lewis, PhD, Marcia A. Testa, MPH, PhD | |||
Rural vs. Urban: Issues in Data Analysis Marion K. Slack, PhD, Irene Guitierrez, BS | |||
Measuring change in multiple outcomes: The case of the Urban Health Initiative Tod Mijanovich, MPA, Winston Lin, MS, Beth Weitzman, PhD | |||
See individual abstracts for presenting author's disclosure statement and author's information. | |||
Organized by: | Statistics | ||
Endorsed by: | Epidemiology; Maternal and Child Health; Mental Health | ||
CE Credits: | CME, Health Education (CHES), Nursing |
The 133rd Annual Meeting & Exposition (December 10-14, 2005) of APHA