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Adaptation of multiple logistic regression to a multiple inverse sampling design: application to the Isfahan healthy heart program.

Authors :
Salehi MM
Levy PS
Jamalzadeh MA
Chang KC
Source :
Statistics in medicine [Stat Med] 2006 Jan 15; Vol. 25 (1), pp. 71-85.
Publication Year :
2006

Abstract

In observational and experimental studies in the health sciences involving human populations, it is sometimes considered desirable to recruit subjects according to designs that specify a predetermined number of subjects in each of several mutually exclusive classes (generally but not necessarily demographic in nature). This type of adaptive sampling design, now generally referred to as multiple inverse sampling (MIS), has received recent attention, and estimation methods are now available for several sequential MIS sampling designs. In this class of designs, subjects are sampled randomly and sequentially, usually one at a time, until all classes have the pre-specified number of subjects. In this paper, we extend MIS for finite population sampling to estimation of the parameters in multiple logistic regression under MIS. Using estimated logistic regression parameters and cost components obtained from the Isfahan Healthy Heart Program (IHHP), we report findings from a simulation experiment in which it appears that, at fixed cost, MIS at the last stage of sampling compares favourably to simple random sampling. The IHHP is a large community intervention study for prevention of cardiovascular disease being conducted in Isfahan, Iran and two other cities in Iran. The IHHP identified subjects through a multistage sample survey in which MIS was used at the final stage of sampling. MIS is one of several methods of adaptive sampling that are generating considerable interest and show promise of being useful in a wide variety of applications.<br /> (Copyright 2005 John Wiley & Sons, Ltd.)

Details

Language :
English
ISSN :
0277-6715
Volume :
25
Issue :
1
Database :
MEDLINE
Journal :
Statistics in medicine
Publication Type :
Academic Journal
Accession number :
16217852
Full Text :
https://doi.org/10.1002/sim.2288