2015 APHA Annual Meeting & Expo

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Recorded Annual Meeting Presentations (RAMP) are now available for purchase.
Only $90 for presenters, $140 for registered attendees and $200 for non-attendees.

Online Program

317008
More Efficient Logistic Analysis Using Moving Extreme Ranked Set Sampling: Application to Children obesity


Monday, November 2, 2015 : 3:10 p.m. - 3:30 p.m.

Hani Samawi, PhD, P.O.Box 8015, Jiann-Ping Hus College of Public Health, Georgia Southern University, Statesboro, GA
Haresh Rochani, DrPH, MPH , M.B.B.S., Department of BIo-statistics, Georgia Southern University, Statesboro, GA
Daniel Linder, PhD, Department of Biostatistics, Georgia Southern University, Statesboro, GA
JingJing Yin, PhD, Department of Bio-statistics, Georgia Southern University, Statesboro, GA
Lili Yu, Ph.D, Biostatistics, Georgia Southern University, Statesboro, GA
Arpita Chatterjee, Ph.D, Mathematics, Georgia Southern University, Statesboro, GA
Robert Vogel, Professor, Department of BIo-statistics, Georgia Southern University, Statesboro, GA
Audio (mp3) recording Recorded Presentation (mp4)
Logistic regression is wildly used for analyzing dichotomous responses, has been intensively applied in social, medical, behavioral and public health sciences research. The paper provides a more efficient logistic regression analysis of a set of predictors based on subjects selected using Moving Extreme Ranked Set Sampling (MERSS) scheme by ranking on one of the available axillary variable know to be associated with the variable of interest (response variable). The paper shows that this approach will provide more powerful testing procedure as well as more efficient odds ratio and parameter estimation than using simple random sample (SRS).  Theoretical derivation and simulation studies will be provided.  Real data from childern health survey are used to illustrate the procedures developed in this paper.

Learning Areas:

Biostatistics, economics
Epidemiology

Learning Objectives:
Demonstrate that using moving extreme ranked set sampling scheme in public health data collection provides more efficient logistic regression analysis

Keyword(s): Child/Adolescent Mental Health, Statistics

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a full professor of Biostatistics and I am the author of more than 75 paper and chapter books in the field of biostatistics methodology and modeling and secondary data analysis
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

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