Adjusted logistic propensity weighting methods for population inference using nonprobability volunteer‐based epidemiologic cohorts
dc.contributor.author | Wang, Lingxiao | |
dc.contributor.author | Valliant, Richard | |
dc.contributor.author | Li, Yan | |
dc.date.accessioned | 2021-11-02T00:46:57Z | |
dc.date.available | 2022-11-01 20:46:56 | en |
dc.date.available | 2021-11-02T00:46:57Z | |
dc.date.issued | 2021-10-30 | |
dc.identifier.citation | Wang, Lingxiao; Valliant, Richard; Li, Yan (2021). "Adjusted logistic propensity weighting methods for population inference using nonprobability volunteer‐based epidemiologic cohorts." Statistics in Medicine 40(24): 5237-5250. | |
dc.identifier.issn | 0277-6715 | |
dc.identifier.issn | 1097-0258 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/170864 | |
dc.publisher | John Wiley & Sons, Inc. | |
dc.subject.other | variance estimation | |
dc.subject.other | finite population inference | |
dc.subject.other | nonprobability sample | |
dc.subject.other | propensity score weighting | |
dc.subject.other | survey sampling | |
dc.title | Adjusted logistic propensity weighting methods for population inference using nonprobability volunteer‐based epidemiologic cohorts | |
dc.type | Article | |
dc.rights.robots | IndexNoFollow | |
dc.subject.hlbsecondlevel | Medicine (General) | |
dc.subject.hlbsecondlevel | Statistics and Numeric Data | |
dc.subject.hlbsecondlevel | Public Health | |
dc.subject.hlbtoplevel | Science | |
dc.subject.hlbtoplevel | Social Sciences | |
dc.subject.hlbtoplevel | Health Sciences | |
dc.description.peerreviewed | Peer Reviewed | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/170864/1/sim9122_am.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/170864/2/sim9122-sup-0001-supinfo.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/170864/3/sim9122.pdf | |
dc.identifier.doi | 10.1002/sim.9122 | |
dc.identifier.source | Statistics in Medicine | |
dc.identifier.citedreference | Li Y, Graubard BI, DiGaetano R. Weighting methods for population‐based case–control studies with complex sampling. J Royal Stat Soc Ser C. 2011; 60 ( 2 ): 165 ‐ 185. | |
dc.identifier.citedreference | Collins R. What makes UK Biobank special. Lancet. 2012; 379 ( 9822 ): 1173 ‐ 1174. | |
dc.identifier.citedreference | Fry A, Littlejohns TJ, Sudlow C, et al. Comparison of sociodemographic and health‐related characteristics of UK Biobank participants with those of the general population. Am J Epidemiol. 2017; 186 ( 9 ): 1026 ‐ 1034. | |
dc.identifier.citedreference | Elliott MR, Valliant R. Inference for nonprobability samples. Stat Sci. 2017; 32 ( 2 ): 249 ‐ 264. | |
dc.identifier.citedreference | Chen Y, Li P, Wu C. Doubly robust inference with nonprobability survey samples. J Am Stat Assoc. 2019; 115 ( 532 ): 2011 ‐ 2021. | |
dc.identifier.citedreference | Wang L, Graubard BI, Katki H, Li Y. Improving external validity of epidemiologic cohort analyses: a kernel weighting approach. J Royal Stat Soc Ser A. 2020; 183 ( 3 ): 1293 – 1311. https://doi.org/10.1111/rssa.12564. | |
dc.identifier.citedreference | Wang L, Graubard BI, Katki HA, Li Y. Efficient and robust propensity‐score‐based methods for population inference using epidemiologic cohorts; 2021. arXiv preprint arXiv:2011.14850. | |
dc.identifier.citedreference | Valliant R, Dever JA. Estimating propensity adjustments for volunteer web surveys. Sociol Methods Res. 2011; 40 ( 1 ): 105 ‐ 137. | |
dc.identifier.citedreference | Valliant R. Comparing alternatives for estimation from nonprobability samples. J SurvStat Methodol. 2020; 8 ( 2 ): 231 ‐ 263. | |
dc.identifier.citedreference | Binder DA. On the variances of asymptotically normal estimators from complex surveys. Int Stat Rev. 1983; 51 ( 3 ): 279 ‐ 292. | |
dc.identifier.citedreference | Chambers RA, Skinner CJ. Sec. 6.3 Analysis of Survey Data. New York, NY: Wiley; 2003. | |
dc.identifier.citedreference | Beaumont JF. Calibrated imputation in surveys under a quasi‐model‐assisted approach. J Royal Stat Soc Ser B. 2005; 67 ( 3 ): 445 ‐ 458. | |
dc.identifier.citedreference | Kim JK, Kim JJ. Nonresponse weighting adjustment using estimated probability. Canadian J Stat. 2007; 35 ( 4 ): 501 ‐ 514. | |
dc.identifier.citedreference | Krewski D, Rao JN. Inference from stratified samples: properties of the linearization, jackknife and balanced repeated replication methods. Ann Stat. 1981; 9 ( 5 ): 1010 ‐ 1019. | |
dc.identifier.citedreference | Scott AJ, Wild CJ. Fitting logistic models under case‐control or choice based sampling. J Royal Stat Soc Ser B. 1986; 48 ( 2 ): 170 ‐ 182. | |
dc.identifier.citedreference | Wang L. Improving External Validity of Epidemiologic Analyses by Incorporating Data from Population‐Based Surveys [Doctoral dissertation]. University of Maryland, College Park; 2020. https://drum.lib.umd.edu/handle/1903/26125. | |
dc.identifier.citedreference | Massey JT. Design and estimation for the national health interview survey, 1985–94. US Department of Health and Human Services, Public Health Service, Centers for Disease Control, National Center for Health Statistics; 1989. | |
dc.identifier.citedreference | Ezzati TM, Massey JT, Waksberg J, Chu A, Maurer KR. Sample design: third National Health and nutrition examination survey. Vital Health Stat Ser 2 Data Eval Methods Res. 1992; 113: 1 ‐ 35. | |
dc.identifier.citedreference | Hartley HO, Rao JN, Kiefer G. Variance estimation with one unit per stratum. J Am Stat Assoc. 1969; 64 ( 327 ): 841 ‐ 851. | |
dc.identifier.citedreference | National Center for Health Statistics. National Death Index User’s Guide. Hyattsville, MD: National Center for Health Statistics; 2013. https://www.cdc.gov/nchs/data/ndi/ndi_users_guide.pdf. Accessed April 2021. | |
dc.identifier.citedreference | National Center for Health Statistics. Data Linkage Public‐Use Linked Mortality File Data Dictionary. Hyattsville, MD: National Center for Health Statistics; 2015. https://www.cdc.gov/nchs/data/datalinkage/public‐use‐2015‐linked‐mortality‐files‐data‐dictionary.pdf. Accessed April 2021. | |
dc.identifier.citedreference | National Center for Health Statistic. Data Linkage Underlying and Multiple Cause of Death Codes. Hyattsville, MD: National Center for Health Statistics; 2018. https://www.cdc.gov/nchs/data/datalinkage/underlying_and_multiple_cause_of_death_codes.pdf. Accessed April 2021. | |
dc.identifier.citedreference | Lee S, Valliant R. Estimation for volunteer panel web surveys using propensity score adjustment and calibration adjustment. Sociol Methods Res. 2009; 37 ( 3 ): 319 ‐ 343. | |
dc.identifier.citedreference | Rivers D. Sampling for web surveys. Paper presented at: Proceedings of the Joint Statistical Meetings, Section on Survey Research Methods; 2007; Salt Lake City, Utah. | |
dc.working.doi | NO | en |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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