Point source modeling of matched case–control data with multiple disease subtypes
dc.contributor.author | Li, Shi | en_US |
dc.contributor.author | Mukherjee, Bhramar | en_US |
dc.contributor.author | Batterman, Stuart | en_US |
dc.date.accessioned | 2012-12-11T17:37:19Z | |
dc.date.available | 2014-02-03T16:21:44Z | en_US |
dc.date.issued | 2012-12-10 | en_US |
dc.identifier.citation | Li, Shi; Mukherjee, Bhramar; Batterman, Stuart (2012). "Point source modeling of matched case–control data with multiple disease subtypes." Statistics in Medicine 31(28): 3617-3637. <http://hdl.handle.net/2027.42/94459> | en_US |
dc.identifier.issn | 0277-6715 | en_US |
dc.identifier.issn | 1097-0258 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/94459 | |
dc.publisher | John Wiley & Sons, Ltd | en_US |
dc.subject.other | Asthma Cases | en_US |
dc.subject.other | Conditional Likelihood | en_US |
dc.subject.other | Disease Subclassification | en_US |
dc.subject.other | Iteratively Reweighted Least Square | en_US |
dc.subject.other | Markov Chain Monte Carlo | en_US |
dc.subject.other | Matched Case–Control | en_US |
dc.subject.other | Point Source Modeling | en_US |
dc.title | Point source modeling of matched case–control data with multiple disease subtypes | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Statistics and Numeric Data | en_US |
dc.subject.hlbsecondlevel | Public Health | en_US |
dc.subject.hlbsecondlevel | Medicine (General) | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.subject.hlbtoplevel | Social Sciences | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.identifier.pmid | 22826092 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/94459/1/sim5388.pdf | |
dc.identifier.doi | 10.1002/sim.5388 | en_US |
dc.identifier.source | Statistics in Medicine | en_US |
dc.identifier.citedreference | Agresti A. Categorical Data Analysis. Wiley: New York, 2002. | en_US |
dc.identifier.citedreference | Breslow NE, Day NE. Statistical methods in cancer research. Volume I – The analysis of case‐control studies. IARC Scientific Publications 1980; 32: 335 – 338. | en_US |
dc.identifier.citedreference | Barnard GA. Contribution to the discussion of Professor Bartlett's paper. Journal of the Royal Statistical Society B 1963; 25: 294. | en_US |
dc.identifier.citedreference | Gallant AR. Nonlinear Statistical Models. Wiley: New York, 1987. | en_US |
dc.identifier.citedreference | Rice KM. Equivalence between conditional and mixture approaches to the Rasch model and matched case‐control studies, with applications. Journal of the American Statistical Association 2004; 99: 510 – 522. | en_US |
dc.identifier.citedreference | Rice KM. Equivalence between conditional and random‐effects likelihoods for pair‐matched case‐control studies. Journal of the American Statistical Association 2008; 103: 385 – 396. | en_US |
dc.identifier.citedreference | Gelman A, Rubin DB. Inference from iterative simulation using multiple sequences. Statistical Science 1992; 7: 457 – 511. | en_US |
dc.identifier.citedreference | Congdon P. Applied Bayesian Modelling. Wiley: New York, 2003. | en_US |
dc.identifier.citedreference | Lawson AB, Browne WJ, Vidal Rodeiro CL. Disease Mapping with WinBugs and MlWin. Wiley: New York, 2003. | en_US |
dc.identifier.citedreference | Diggle PJ, Rowlingson BS. A conditional approach to point process modeling of raised incidence. Journal of the Royal Statistical Society A 1994; 157: 433 – 440. | en_US |
dc.identifier.citedreference | Diggle PJ, Elliott P, Morris SE, Shaddick G. Regression modeling of disease risk in relation to point sources. Journal of the Royal Statistical Society A 1997; 160: 491 – 505. | en_US |
dc.identifier.citedreference | Diggle PJ, Morris SE, Wakefield J. Point‐source modeling using matched case‐control data. Biostatistics 2000; 1: 89 – 105. | en_US |
dc.identifier.citedreference | Diggle PJ, Moyeed RA, Tawn JA. Model‐based geostatistics (with discussion). Applied Statistics 1998; 47: 299 – 350. | en_US |
dc.identifier.citedreference | Wakefield JC, Morris SE. The Bayesian modelling of disease risk in relation to a point source. Journal of the American Statistical Association 2001; 96: 77 – 91. | en_US |
dc.identifier.citedreference | Dreassi E, Lagazio C, Maule M, Magnani C, Biggeri A. Sensitivity analysis of the relationship between disease occurrence and distance from a putative source of pollution. Geospatial Health 2008; 2: 263 – 271. | en_US |
dc.identifier.citedreference | Rodrigues A, Diggle PJ, Assuncao R. Semi‐parametric approach to point source modeling in epidemiology and criminology. Journal of the Royal Statistical Society C 2010; 59: 533 – 542. | en_US |
dc.identifier.citedreference | Li S, Batterman S, Wasilevich E, Elasaad H, Wahl R, Mukherjee B. Asthma exacerbation and proximity of residence to major roads: a population‐based matched case‐control study among the pediatric Medicaid population in Detroit, Michigan. Environmental Health 2011; 10: 34. DOI: 10.1186/1476‐069X‐10‐34. | en_US |
dc.identifier.citedreference | Wu YC, Batterman S. Proximity of schools in Detroit, Michigan to automobile and truck traffic. Journal of Exposure Science and Environmental Epidemiology 2006; 16: 457 – 470. | en_US |
dc.identifier.citedreference | Diciccio TJ, Kass RE, Raftery AE, Wasserman L. Computing Bayes factors by combining simulation and asymptotic approximations. Journal of the American Statistical Association 1997; 92: 903 – 915. | en_US |
dc.identifier.citedreference | Kass RE, Raftery AE, Bayes factors. Journal of the American Statistical Association 1995; 90: 773 – 795. | en_US |
dc.identifier.citedreference | Breslow NE, Day NE, Halvorsen KT, Prentice RL, Sabai C. Estimation of multiple relative risk functions in matched case‐control studies. American Journal of Epidemiology 1978; 108: 299 – 307. | en_US |
dc.identifier.citedreference | Liang KY, Stewart W. Polychotomous logistic regression methods for matched case‐control studies with multiple case or control groups. American Journal of Epidemiology 1987; 125: 720 – 730. | en_US |
dc.identifier.citedreference | Becher J, Jockel KH. Bias adjustment with polychotomous logistic regression in matched case‐control studies with two control groups. Biometrical Journal 1990; 7: 801 – 816. | en_US |
dc.identifier.citedreference | Becher H. Alternative parameterization of polychotomous models: theory and application to matched case‐control studies. Statistics in Medicine 1991; 10: 375 – 382. | en_US |
dc.identifier.citedreference | Thomas DC, Goldberg M, Dewar R, Siemiatycki J. Statistical methods relating several exposure factors to several diseases in case‐heterogeneity studies. Statistics in Medicine 1986; 5: 49 – 60. | en_US |
dc.identifier.citedreference | Durbin N, Pasternack BS. Risk assessment for case‐control subgroups by polychotomous logistic regression. American Journal of Epidemiology 1986; 6: 1101 – 1117. | en_US |
dc.identifier.citedreference | Sinha S, Mukherjee B, Ghosh M. Bayesian semiparametric modeling for matched case‐control studies with multiple disease states. Biometrics 2004; 60: 41 – 49. | en_US |
dc.identifier.citedreference | Mukherjee B, Liu I, Sinha S. Analysis of matched case‐control data with multiple ordered disease states: possible choices and comparisons. Statistics in Medicine 2007; 26: 3240 – 3257. | en_US |
dc.identifier.citedreference | Mukherjee B, Ahn J, Liu I, Sanchez BN. On elimination of nuisance parameters in stratified proportional odds model by amalgamating conditional likelihoods. Statistics in Medicine 2008; 27: 4950 – 4971. | en_US |
dc.identifier.citedreference | Diggle PJ. A point process modeling approach to raised incidence of a rare phenomenon in the vicinity of a pre‐specified point. Journal of the Royal Statistical Society A 1990; 153: 349 – 362. | en_US |
dc.identifier.citedreference | Lawson AB. On the analysis of mortality events associated with a pre‐specified fixed point. Journal of the Royal Statistical Society A 1993; 156: 363 – 377. | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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