Adjusted logistic propensity weighting methods for population inference using nonprobability volunteer-based epidemiologic cohorts.
Adjusted logistic propensity weighting methods for population inference using nonprobability volunteer-based epidemiologic cohorts.
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DOI:
10.1002/sim.9122
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发表时间:
2021-10-30
影响因子:
2
通讯作者:
Li Y
中科院分区:
文献类型:
--
作者:
Wang L;Valliant R;Li Y
Many epidemiologic studies forgo probability sampling and turn to nonprobability volunteer-based samples because of cost, response burden, and invasiveness of biological samples. However, finite population (FP) inference is difficult to make from the nonprobability sample due to the lack of population representativeness. Aiming for making inferences at the population level using nonprobability samples, various inverse propensity score weighting methods have been studied with the propensity defined by the participation rate of population units in the nonprobability sample. In this article, we propose an adjusted logistic propensity weighting (ALP) method to estimate the participation rates for nonprobability sample units. The proposed ALP method is easy to implement by ready-to-use software while producing approximately unbiased estimators for population quantities regardless of the nonprobability sample rate. The efficiency of the ALP estimator can be further improved by scaling the survey sample weights in propensity estimation. Taylor linearization variance estimators are proposed for ALP estimators of FP means that account for all sources of variability. The proposed ALP methods are evaluated numerically via simulation studies and empirically using the naïve unweighted National Health and Nutrition Examination Survey III sample, while taking the 1997 National Health Interview Survey as the reference, to estimate the 15-year mortality rates.
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DOI:
10.1111/rssa.12564
发表时间:
2020-06
期刊:
Journal of the Royal Statistical Society. Series A, (Statistics in Society)
影响因子:
--
作者:
Wang L;Graubard BI;Katki HA;Li Y
通讯作者:
Li Y
影响因子:
5
作者:
Fry A;Littlejohns TJ;Sudlow C;Doherty N;Adamska L;Sprosen T;Collins R;Allen NE
通讯作者:
Allen NE
DOI:
10.1111/j.1467-9876.2010.00731.x
发表时间:
2011-01-01
影响因子:
1.6
作者:
Li, Yan;Graubard, Barry I.;DiGaetano, Ralph
通讯作者:
DiGaetano, Ralph
影响因子:
6.3
作者:
Valliant, Richard;Dever, Jill A.
通讯作者:
Dever, Jill A.
影响因子:
3.7
作者:
HARTLEY, HO;RAO, JNK;KIEFER, G
通讯作者:
KIEFER, G