Statistical Methods for Generalized Linear Models with Covariates Subject to Detection Limits
Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we...
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| Published in | Statistics in biosciences Vol. 7; no. 1; pp. 68 - 89 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
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Springer US
01.05.2015
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| Abstract | Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study. |
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| AbstractList | Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study.Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study. Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study. |
| Author | Zhang, Daowen Bernhardt, Paul W. Wang, Huixia J. |
| Author_xml | – sequence: 1 givenname: Paul W. surname: Bernhardt fullname: Bernhardt, Paul W. organization: Department of Mathematics and Statistics, Villanova University – sequence: 2 givenname: Huixia J. surname: Wang fullname: Wang, Huixia J. email: hwang3@ncsu.edu organization: Department of Statistics, North Carolina State University – sequence: 3 givenname: Daowen surname: Zhang fullname: Zhang, Daowen organization: Department of Statistics, North Carolina State University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26257836$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1007/s10651-012-0191-6 10.1111/1467-9876.00207 10.1097/EDE.0b013e3181ce97d8 10.1111/j.0006-341X.1999.00625.x 10.1046/j.1467-9876.2003.05168.x 10.1002/(SICI)1097-0258(19990915/30)18:17/18<2435::AID-SIM267>3.0.CO;2-B 10.1289/ehp.7199 10.2307/3315865 10.1198/0003130031450 10.1214/07-AOS564 10.1093/biomet/65.1.141 10.1093/infdis/175.2.247 10.1198/jbes.2009.06119 10.1198/016214501750332866 10.2307/2533289 10.1080/01621459.2011.643198 10.1002/1097-0258(20010115)20:1<33::AID-SIM640>3.0.CO;2-O 10.1093/biomet/73.3.635 10.1002/sim.1923 10.1016/j.csda.2011.11.010 10.1002/sim.4280 10.1002/sim.901 10.1002/cjs.5550340408 10.1093/biomet/85.4.935 10.1198/016214502388618744 10.1080/1047322X.1990.10389587 10.1002/1521-4036(200209)44:6<657::AID-BIMJ657>3.0.CO;2-Z 10.1093/biomet/87.1.113 10.1002/sim.1601 10.1001/archinte.167.15.1655 10.1214/08-AOS657 10.1093/biomet/80.1.27 10.1002/sim.4503 10.1080/02664763.2012.681362 10.1111/j.1468-2354.2007.00470.x 10.1198/016214504000001844 |
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| References | Lyles, Lyles, Taylor (CR20) 2000; 49 Hughes (CR12) 1999; 55 Herring, Ibrahim, Lipsitz (CR9) 2004; 53 Clayton (CR4) 1978; 65 Austin, Hoch (CR3) 2004; 23 Wu, Chen, Ware, Koyama (CR41) 2012; 39 Tsiatis (CR36) 2006 CR10 Lyles, Fan, Chauchoowon (CR21) 2001; 20 Wang, Feng (CR38) 2012; 107 Wu (CR42) 2002; 97 Nie, Chu, Liu, Cole, Vexler, Schisterman (CR26) 2010; 21S Robins, Wang (CR32) 2000; 87 Ibrahim, Chen, Lipsitz, Herring (CR14) 2005; 100 Nan, Kalbfleisch, Yu (CR25) 2009; 37 Schaubel, Cai (CR34) 2006; 34 Tsimikas, Bantis, Georgiou (CR37) 2012; 56 Pettitt (CR28) 1986; 73 Helsel (CR7) 2012 Wang, Fygenson (CR39) 2009; 37 Ibrahim, Chen, Lipsitz (CR13) 2002; 30 CR6 Lee, Kong, Weissfeld (CR16) 2012; 31 Hornung, Reed (CR11) 1990; 5 Piepho, Thoni, Müller (CR29) 2002; 44 Rigobon, Stoker (CR31) 2009; 27 Rubin (CR33) 1987 May, Ibrahim, Chu (CR23) 2011; 30 Herring, Ibrahim (CR8) 2001; 96 Lynn (CR22) 2001; 20 Rigobon, Stoker (CR30) 2007; 48 Moulton, Halsey (CR24) 1995; 51 Arunajadai, Rauh (CR1) 2012; 157 Firth (CR5) 1993; 23 Paxton, Coombs, McElrath, Keefer, Hughes, Sinagil, Chernoff, Demeter, Williams, Corey (CR27) 1997; 175 Wang, Robins (CR40) 1998; 84 Austin, Brunner (CR2) 2003; 57 Thiebaut, Jacqmin-Gadda, Babiker, Commenges (CR35) 2005; 24 Little (CR18) 1992; 87 Lipsitz, Ibrahim, Chen, Peterson (CR17) 1999; 18 Lubin, Colt, Camann, Davis, Cerhan, Severson, Bernstein, Hartge (CR19) 2004; 112 Kellum, Kong, Fink, Weissfeld, Yealy, Pinsky, Fine, Krichevsky, Delude, Angus (CR15) 2007; 167 9099_CR10 RH Lyles (9099_CR20) 2000; 49 DB Rubin (9099_CR33) 1987 H Wang (9099_CR38) 2012; 107 WB Paxton (9099_CR27) 1997; 175 R Rigobon (9099_CR31) 2009; 27 JH Lubin (9099_CR19) 2004; 112 H Wu (9099_CR41) 2012; 39 AH Herring (9099_CR8) 2001; 96 PC Austin (9099_CR2) 2003; 57 PC Austin (9099_CR3) 2004; 23 JG Ibrahim (9099_CR14) 2005; 100 AA Tsiatis (9099_CR36) 2006 JA Kellum (9099_CR15) 2007; 167 B Nan (9099_CR25) 2009; 37 H-P Piepho (9099_CR29) 2002; 44 D Firth (9099_CR5) 1993; 23 AH Herring (9099_CR9) 2004; 53 JP Hughes (9099_CR12) 1999; 55 RC May (9099_CR23) 2011; 30 RW Hornung (9099_CR11) 1990; 5 M Lee (9099_CR16) 2012; 31 JM Robins (9099_CR32) 2000; 87 SR Lipsitz (9099_CR17) 1999; 18 RJA Little (9099_CR18) 1992; 87 DG Clayton (9099_CR4) 1978; 65 SG Arunajadai (9099_CR1) 2012; 157 LH Moulton (9099_CR24) 1995; 51 JG Ibrahim (9099_CR13) 2002; 30 N Wang (9099_CR40) 1998; 84 H Wang (9099_CR39) 2009; 37 DR Helsel (9099_CR7) 2012 R Rigobon (9099_CR30) 2007; 48 HS Lynn (9099_CR22) 2001; 20 L Wu (9099_CR42) 2002; 97 DE Schaubel (9099_CR34) 2006; 34 R Thiebaut (9099_CR35) 2005; 24 RH Lyles (9099_CR21) 2001; 20 L Nie (9099_CR26) 2010; 21S AN Pettitt (9099_CR28) 1986; 73 9099_CR6 JV Tsimikas (9099_CR37) 2012; 56 10474151 - Stat Med. 1999 Sep 15-30;18(17-18):2435-48 21710558 - Stat Med. 2011 Sep 10;30(20):2551-61 21422965 - Epidemiology. 2010 Jul;21 Suppl 4:S17-24 23049157 - J Appl Stat. 2012;39(8):1733-1747 11568949 - Stat Med. 2001 Oct 15;20(19):2921-33 8589241 - Biometrics. 1995 Dec;51(4):1570-8 11135346 - Stat Med. 2001 Jan 15;20(1):33-45 15579415 - Environ Health Perspect. 2004 Dec;112(17):1691-6 22359320 - Stat Med. 2012 Jul 30;31(17):1838-48 17698689 - Arch Intern Med. 2007 Aug 13-27;167(15):1655-63 9203644 - J Infect Dis. 1997 Feb;175(2):247-54 11318225 - Biometrics. 1999 Jun;55(2):625-9 14748036 - Stat Med. 2004 Feb 15;23(3):411-29 15523706 - Stat Med. 2005 Jan 15;24(1):65-82 |
| References_xml | – volume: 157 start-page: 369 year: 2012 end-page: 391 ident: CR1 article-title: Handling covariates subject to limits of detection in regression publication-title: Environ Ecol Stat doi: 10.1007/s10651-012-0191-6 – volume: 49 start-page: 485 year: 2000 end-page: 497 ident: CR20 article-title: Random regression models for human immunodeficiency virus ribonucleic acid data subject to left censoring and informative drop-outs publication-title: J R Stat Soc, Ser C, Appl Stat doi: 10.1111/1467-9876.00207 – year: 2012 ident: CR7 publication-title: Statistics for censored environmental data using minitab and R – volume: 21S start-page: S17 year: 2010 end-page: S24 ident: CR26 article-title: Linear regression with an independent variable subject to a detection limit publication-title: Epidemiology doi: 10.1097/EDE.0b013e3181ce97d8 – volume: 55 start-page: 625 year: 1999 end-page: 629 ident: CR12 article-title: Mixed effects models with censored data with application to HIV RNA levels publication-title: Biometrics doi: 10.1111/j.0006-341X.1999.00625.x – volume: 53 start-page: 293 year: 2004 end-page: 310 ident: CR9 article-title: Non-ignorable missing covariate data in survival analysis: a case-study of an international breast cancer study group trial publication-title: J R Stat Soc, Ser C, Appl Stat doi: 10.1046/j.1467-9876.2003.05168.x – volume: 18 start-page: 2435 year: 1999 end-page: 2448 ident: CR17 article-title: Non-ignorable missing covariates in generalized linear models publication-title: Stat Med doi: 10.1002/(SICI)1097-0258(19990915/30)18:17/18<2435::AID-SIM267>3.0.CO;2-B – volume: 112 start-page: 1691 year: 2004 end-page: 1696 ident: CR19 article-title: Epidemiologic evaluation of measurement data in the presence of detection limits publication-title: Environ Health Perspect doi: 10.1289/ehp.7199 – volume: 30 start-page: 55 year: 2002 end-page: 78 ident: CR13 article-title: Bayesian methods for generalized linear models with covariates missing at random publication-title: Can J Stat doi: 10.2307/3315865 – volume: 57 start-page: 97 year: 2003 end-page: 104 ident: CR2 article-title: Type I error inflation in the presence of a ceiling effect publication-title: Am Stat doi: 10.1198/0003130031450 – ident: CR10 – volume: 37 start-page: 756 year: 2009 end-page: 781 ident: CR39 article-title: Inference for censored quantile regression models in longitudinal studies publication-title: Ann Stat doi: 10.1214/07-AOS564 – volume: 65 start-page: 677 year: 1978 end-page: 692 ident: CR4 article-title: A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence publication-title: Biometrika doi: 10.1093/biomet/65.1.141 – ident: CR6 – volume: 175 start-page: 247 year: 1997 end-page: 254 ident: CR27 article-title: Longitudinal analysis of quantitative virologic measures in human immunodeficiency virus-infected subjects with ≥400 cd4 lymphocytes: implications for applying measurements to individual patients publication-title: J Infect Dis doi: 10.1093/infdis/175.2.247 – volume: 27 start-page: 340 year: 2009 end-page: 353 ident: CR31 article-title: Bias from censored regressors publication-title: J Bus Econ Stat doi: 10.1198/jbes.2009.06119 – volume: 96 start-page: 292 year: 2001 end-page: 302 ident: CR8 article-title: Likelihood-based methods for missing covariates in the Cox proportional hazards model publication-title: J Am Stat Assoc doi: 10.1198/016214501750332866 – volume: 51 start-page: 1570 year: 1995 end-page: 1578 ident: CR24 article-title: A mixture model with detection limits for regression analysis of antibody response to vaccine publication-title: Biometrics doi: 10.2307/2533289 – volume: 107 start-page: 194 year: 2012 end-page: 204 ident: CR38 article-title: Multiple imputation for m-regression with censored covariates publication-title: J Am Stat Assoc doi: 10.1080/01621459.2011.643198 – volume: 20 start-page: 33 year: 2001 end-page: 45 ident: CR22 article-title: Maximum likelihood inference for left-censored HIV RNA data publication-title: Stat Med doi: 10.1002/1097-0258(20010115)20:1<33::AID-SIM640>3.0.CO;2-O – volume: 87 start-page: 1227 year: 1992 end-page: 1237 ident: CR18 article-title: Regression with missing x’s: a review publication-title: J Am Stat Assoc – volume: 73 start-page: 635 year: 1986 end-page: 643 ident: CR28 article-title: Censored observations, repeated measures and mixed effects models—An approach using the em algorithm and normal errors publication-title: Biometrika doi: 10.1093/biomet/73.3.635 – volume: 24 start-page: 65 year: 2005 end-page: 82 ident: CR35 article-title: Joint modelling of bivariate longitudinal data with informative dropout and left-censoring, with application to the evolution of cd4+ cell count and HIV RNA viral load in response to treatment of HIV infection publication-title: Stat Med doi: 10.1002/sim.1923 – volume: 56 start-page: 1854 year: 2012 end-page: 1868 ident: CR37 article-title: Inference in generalized linear regression models with a censored covariate publication-title: Comput Stat Data Anal doi: 10.1016/j.csda.2011.11.010 – volume: 30 start-page: 2551 year: 2011 end-page: 2561 ident: CR23 article-title: Maximum likelihood estimation in generalized linear models with multiple covariates subject to detection limits publication-title: Stat Med doi: 10.1002/sim.4280 – volume: 20 start-page: 2921 year: 2001 end-page: 2933 ident: CR21 article-title: Correlation coefficient estimation involving a left censored laboratory assay variable publication-title: Stat Med doi: 10.1002/sim.901 – volume: 34 start-page: 677 year: 2006 end-page: 692 ident: CR34 article-title: Multiple imputation methods for recurrent event data with missing event category publication-title: Can J Stat doi: 10.1002/cjs.5550340408 – volume: 84 start-page: 935 year: 1998 end-page: 948 ident: CR40 article-title: Large-sample theory for parametric multiple imputation procedures publication-title: Biometrika doi: 10.1093/biomet/85.4.935 – volume: 97 start-page: 955 year: 2002 end-page: 964 ident: CR42 article-title: A joint model for nonlinear mixed-effects models with censoring and covariates measured with error, with applications to aids studies publication-title: J Am Stat Assoc doi: 10.1198/016214502388618744 – volume: 5 start-page: 46 year: 1990 end-page: 51 ident: CR11 article-title: Estimation of average concentration in the presence of nondetectable values publication-title: Appl Occup Environ Hyg doi: 10.1080/1047322X.1990.10389587 – volume: 44 start-page: 657 year: 2002 end-page: 670 ident: CR29 article-title: Estimating the product-moment correlation in samples with censoring on both variables publication-title: Biom J doi: 10.1002/1521-4036(200209)44:6<657::AID-BIMJ657>3.0.CO;2-Z – volume: 87 start-page: 113 year: 2000 end-page: 124 ident: CR32 article-title: Inference for imputation estimators publication-title: Biometrika doi: 10.1093/biomet/87.1.113 – volume: 23 start-page: 411 year: 2004 end-page: 429 ident: CR3 article-title: Estimating linear regression models in the presence of a censored independent variable publication-title: Stat Med doi: 10.1002/sim.1601 – volume: 167 start-page: 1655 year: 2007 end-page: 1663 ident: CR15 article-title: Understanding the inflammatory cytokine response in pneumonia and sepsis publication-title: Arch Intern Med doi: 10.1001/archinte.167.15.1655 – volume: 37 start-page: 2351 year: 2009 end-page: 2376 ident: CR25 article-title: Asymptotic theory for the semiparametric accelerated failure time model with missing data publication-title: Ann Stat doi: 10.1214/08-AOS657 – volume: 23 start-page: 27 year: 1993 end-page: 38 ident: CR5 article-title: Bias reduction of maximum likelihood estimates publication-title: Biometrika doi: 10.1093/biomet/80.1.27 – volume: 31 start-page: 1838 year: 2012 end-page: 1848 ident: CR16 article-title: Multiple imputation for left-censored biomarker data based on Gibbs sampling method publication-title: Stat Med doi: 10.1002/sim.4503 – year: 1987 ident: CR33 article-title: Multiple imputation for nonresponse publication-title: Surveys – volume: 39 start-page: 1733 year: 2012 end-page: 1747 ident: CR41 article-title: A Bayesian approach for generalized linear models with explanatory biomarker measurement variables subject to detection limit—An application to acute lung injury publication-title: Appl Stat doi: 10.1080/02664763.2012.681362 – volume: 48 start-page: 1441 year: 2007 end-page: 1467 ident: CR30 article-title: Estimation with censored regressors: basic issues publication-title: Int Econ Rev doi: 10.1111/j.1468-2354.2007.00470.x – year: 2006 ident: CR36 publication-title: Semiparametric theory and missing data – volume: 100 start-page: 332 year: 2005 end-page: 346 ident: CR14 article-title: Missing-data methods for generalized linear models: a comparative review publication-title: J Am Stat Assoc doi: 10.1198/016214504000001844 – volume: 87 start-page: 113 year: 2000 ident: 9099_CR32 publication-title: Biometrika doi: 10.1093/biomet/87.1.113 – volume: 23 start-page: 411 year: 2004 ident: 9099_CR3 publication-title: Stat Med doi: 10.1002/sim.1601 – volume: 21S start-page: S17 year: 2010 ident: 9099_CR26 publication-title: Epidemiology doi: 10.1097/EDE.0b013e3181ce97d8 – volume: 23 start-page: 27 year: 1993 ident: 9099_CR5 publication-title: Biometrika doi: 10.1093/biomet/80.1.27 – volume-title: Surveys year: 1987 ident: 9099_CR33 – volume: 24 start-page: 65 year: 2005 ident: 9099_CR35 publication-title: Stat Med doi: 10.1002/sim.1923 – volume: 87 start-page: 1227 year: 1992 ident: 9099_CR18 publication-title: J Am Stat Assoc – volume: 20 start-page: 33 year: 2001 ident: 9099_CR22 publication-title: Stat Med doi: 10.1002/1097-0258(20010115)20:1<33::AID-SIM640>3.0.CO;2-O – ident: 9099_CR10 – volume: 31 start-page: 1838 year: 2012 ident: 9099_CR16 publication-title: Stat Med doi: 10.1002/sim.4503 – volume: 84 start-page: 935 year: 1998 ident: 9099_CR40 publication-title: Biometrika doi: 10.1093/biomet/85.4.935 – volume: 157 start-page: 369 year: 2012 ident: 9099_CR1 publication-title: Environ Ecol Stat doi: 10.1007/s10651-012-0191-6 – ident: 9099_CR6 – volume: 97 start-page: 955 year: 2002 ident: 9099_CR42 publication-title: J Am Stat Assoc doi: 10.1198/016214502388618744 – volume: 44 start-page: 657 year: 2002 ident: 9099_CR29 publication-title: Biom J doi: 10.1002/1521-4036(200209)44:6<657::AID-BIMJ657>3.0.CO;2-Z – volume: 30 start-page: 2551 year: 2011 ident: 9099_CR23 publication-title: Stat Med doi: 10.1002/sim.4280 – volume: 37 start-page: 756 year: 2009 ident: 9099_CR39 publication-title: Ann Stat doi: 10.1214/07-AOS564 – volume: 57 start-page: 97 year: 2003 ident: 9099_CR2 publication-title: Am Stat doi: 10.1198/0003130031450 – volume: 175 start-page: 247 year: 1997 ident: 9099_CR27 publication-title: J Infect Dis doi: 10.1093/infdis/175.2.247 – volume: 53 start-page: 293 year: 2004 ident: 9099_CR9 publication-title: J R Stat Soc, Ser C, Appl Stat doi: 10.1046/j.1467-9876.2003.05168.x – volume: 48 start-page: 1441 year: 2007 ident: 9099_CR30 publication-title: Int Econ Rev doi: 10.1111/j.1468-2354.2007.00470.x – volume: 34 start-page: 677 year: 2006 ident: 9099_CR34 publication-title: Can J Stat doi: 10.1002/cjs.5550340408 – volume: 55 start-page: 625 year: 1999 ident: 9099_CR12 publication-title: Biometrics doi: 10.1111/j.0006-341X.1999.00625.x – volume: 56 start-page: 1854 year: 2012 ident: 9099_CR37 publication-title: Comput Stat Data Anal doi: 10.1016/j.csda.2011.11.010 – volume: 73 start-page: 635 year: 1986 ident: 9099_CR28 publication-title: Biometrika doi: 10.1093/biomet/73.3.635 – volume: 96 start-page: 292 year: 2001 ident: 9099_CR8 publication-title: J Am Stat Assoc doi: 10.1198/016214501750332866 – volume: 167 start-page: 1655 year: 2007 ident: 9099_CR15 publication-title: Arch Intern Med doi: 10.1001/archinte.167.15.1655 – volume-title: Semiparametric theory and missing data year: 2006 ident: 9099_CR36 – volume: 100 start-page: 332 year: 2005 ident: 9099_CR14 publication-title: J Am Stat Assoc doi: 10.1198/016214504000001844 – volume: 27 start-page: 340 year: 2009 ident: 9099_CR31 publication-title: J Bus Econ Stat doi: 10.1198/jbes.2009.06119 – volume: 112 start-page: 1691 year: 2004 ident: 9099_CR19 publication-title: Environ Health Perspect doi: 10.1289/ehp.7199 – volume: 30 start-page: 55 year: 2002 ident: 9099_CR13 publication-title: Can J Stat doi: 10.2307/3315865 – volume: 20 start-page: 2921 year: 2001 ident: 9099_CR21 publication-title: Stat Med doi: 10.1002/sim.901 – volume: 5 start-page: 46 year: 1990 ident: 9099_CR11 publication-title: Appl Occup Environ Hyg doi: 10.1080/1047322X.1990.10389587 – volume: 65 start-page: 677 year: 1978 ident: 9099_CR4 publication-title: Biometrika doi: 10.1093/biomet/65.1.141 – volume: 18 start-page: 2435 year: 1999 ident: 9099_CR17 publication-title: Stat Med doi: 10.1002/(SICI)1097-0258(19990915/30)18:17/18<2435::AID-SIM267>3.0.CO;2-B – volume: 107 start-page: 194 year: 2012 ident: 9099_CR38 publication-title: J Am Stat Assoc doi: 10.1080/01621459.2011.643198 – volume-title: Statistics for censored environmental data using minitab and R year: 2012 ident: 9099_CR7 – volume: 37 start-page: 2351 year: 2009 ident: 9099_CR25 publication-title: Ann Stat doi: 10.1214/08-AOS657 – volume: 39 start-page: 1733 year: 2012 ident: 9099_CR41 publication-title: Appl Stat doi: 10.1080/02664763.2012.681362 – volume: 49 start-page: 485 year: 2000 ident: 9099_CR20 publication-title: J R Stat Soc, Ser C, Appl Stat doi: 10.1111/1467-9876.00207 – volume: 51 start-page: 1570 year: 1995 ident: 9099_CR24 publication-title: Biometrics doi: 10.2307/2533289 – reference: 21422965 - Epidemiology. 2010 Jul;21 Suppl 4:S17-24 – reference: 11568949 - Stat Med. 2001 Oct 15;20(19):2921-33 – reference: 10474151 - Stat Med. 1999 Sep 15-30;18(17-18):2435-48 – reference: 11318225 - Biometrics. 1999 Jun;55(2):625-9 – reference: 9203644 - J Infect Dis. 1997 Feb;175(2):247-54 – reference: 11135346 - Stat Med. 2001 Jan 15;20(1):33-45 – reference: 17698689 - Arch Intern Med. 2007 Aug 13-27;167(15):1655-63 – reference: 8589241 - Biometrics. 1995 Dec;51(4):1570-8 – reference: 23049157 - J Appl Stat. 2012;39(8):1733-1747 – reference: 15523706 - Stat Med. 2005 Jan 15;24(1):65-82 – reference: 15579415 - Environ Health Perspect. 2004 Dec;112(17):1691-6 – reference: 21710558 - Stat Med. 2011 Sep 10;30(20):2551-61 – reference: 22359320 - Stat Med. 2012 Jul 30;31(17):1838-48 – reference: 14748036 - Stat Med. 2004 Feb 15;23(3):411-29 |
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| Title | Statistical Methods for Generalized Linear Models with Covariates Subject to Detection Limits |
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