يعرض 1 - 9 نتائج من 9 نتيجة بحث عن '"Ritter, Victor S."', وقت الاستعلام: 1.24s تنقيح النتائج
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    المؤلفون: Walmer, Rachel W.1 (AUTHOR) anush.narasimhansridharan@fccc.edu, Ritter, Victor S.2 (AUTHOR), Sridharan, Anush1,3 (AUTHOR), Kasoji, Sandeep K.1,4 (AUTHOR), Altun, Ersan5 (AUTHOR) ersan_altun@med.unc.edu, Lee, Ellie5 (AUTHOR) kristen_olinger@med.unc.edu, Olinger, Kristen5 (AUTHOR), Wagner, Sean5 (AUTHOR), Radhakrishna, Roshni6 (AUTHOR) emily_chang@med.unc.edu, Johnson, Kennita A.1 (AUTHOR), Rathmell, W. Kimryn7 (AUTHOR), Qaqish, Bahjat2 (AUTHOR), Dayton, Paul A.1 (AUTHOR), Chang, Emily H.6 (AUTHOR)

    المصدر: Journal of Clinical Medicine. Oct2023, Vol. 12 Issue 20, p6494. 12p.

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    وصف الملف: application/pdf

    العلاقة: Chen, Ling-Wan; Fine, Jason P.; Bair, Eric; Ritter, Victor S.; McElrath, Thomas F.; Cantonwine, David E.; Meeker, John D.; Ferguson, Kelly K.; Zhao, Shanshan (2022). "Semiparametric analysis of a generalized linear model with multiple covariates subject to detection limits." Statistics in Medicine 41(24): 4791-4808.; https://hdl.handle.net/2027.42/175059Test; Statistics in Medicine; Chen Q, Wu H, Ware LB, Koyama T. A Bayesian approach for the Cox proportional hazards model with covariates subject to detection limit. Int J Stat Med Res. 2014; 3 ( 1 ): 32.; Ferguson KK, McElrath TF, Meeker JD. Environmental phthalate exposure and preterm birth. JAMA Pediatr. 2014; 168 ( 1 ): 61 - 67.; Ferguson KK, McElrath TF, Chen Y-H, Loch-Caruso R, Mukherjee B, Meeker JD. Repeated measures of urinary oxidative stress biomarkers during pregnancy and preterm birth. Am J Obstet Gynecol. 2015; 212 ( 2 ): 208 - e1.; Kim SS, Meeker JD, Carroll R, et al. Urinary trace metals individually and in mixtures in association with preterm birth. Environ Int. 2018; 121: 582 - 590.; D’Angelo G, Weissfeld L, GenIMS Investigators. An index approach for the Cox model with left censored covariates. Stat Med. 2008; 27 ( 22 ): 4502 - 4514.; Nie L, Chu H, Liu C, Cole SR, Vexler A, Schisterman EF. Linear regression with an independent variable subject to a detection limit. Epidemiology. 2010; 21 ( Suppl 4 ): S17.; Little RJA, Rubin DB. Statistical Analysis with Missing Data. Hoboken: Wiley; 2019.; Helsel DR. Nondetects and Data Analysis. Statistics for Censored Environmental Data. Hoboken: Wiley-Interscience; 2005.; Richardson DB, Ciampi A. Effects of exposure measurement error when an exposure variable is constrained by a lower limit. Am J Epidemiol. 2003; 157 ( 4 ): 355 - 363.; Arunajadai SG, Rauh VA. Handling covariates subject to limits of detection in regression. Environ Ecol Stat. 2012; 19 ( 3 ): 369 - 391.; Cole SR, Chu H, Nie L, Schisterman EF. Estimating the odds ratio when exposure has a limit of detection. Int J Epidemiol. 2009; 38 ( 6 ): 1674 - 1680.; Sattar A, Sinha SK, Wang X-F, Li Y. Frailty models for pneumonia to death with a left-censored covariate. Stat Med. 2015; 34 ( 14 ): 2266 - 2280.; Vexler A, Liu A, Eliseeva E, Schisterman EF. Maximum likelihood ratio tests for comparing the discriminatory ability of biomarkers subject to limit of detection. Biometrics. 2008; 64 ( 3 ): 895 - 903.; Kong S, Nan B. Semiparametric approach to regression with a covariate subject to a detection limit. Biometrika. 2016; 103 ( 1 ): 161 - 174.; Atem FD, Qian J, Maye JE, Johnson KA, Betensky RA. Linear regression with a randomly censored covariate: application to an Alzheimer’s study. J Royal Stat Soc Ser C (Appl Stat). 2017; 66 ( 2 ): 313 - 328.; Atem FD, Matsouaka RA, Zimmern VE. Cox regression model with randomly censored covariates. Biom J. 2019; 61 ( 4 ): 1020 - 1032.; Ding Y, Kong S, Kang S, Chen W. A semiparametric imputation approach for regression with censored covariate with application to an AMD progression study. Stat Med. 2018; 37 ( 23 ): 3293 - 3308.; May RC, Ibrahim JG, Chu H. Maximum likelihood estimation in generalized linear models with multiple covariates subject to detection limits. Stat Med. 2011; 30 ( 20 ): 2551 - 2561.; Wu H, Chen Q, Ware LB, Koyama T. A Bayesian approach for generalized linear models with explanatory biomarker measurement variables subject to detection limit: an application to acute lung injury. J Appl Stat. 2012; 39 ( 8 ): 1733 - 1747.; Lee M, Kong L, Weissfeld L. Multiple imputation for left-censored biomarker data based on Gibbs sampling method. Stat Med. 2012; 31 ( 17 ): 1838 - 1848.; Bernhardt PW, Wang HJ, Zhang D. Flexible modeling of survival data with covariates subject to detection limits via multiple imputation. Comput Stat Data Anal. 2014; 69: 81 - 91.; Bartlett JW, Seaman SR, White IR, Carpenter JR, Alzheimer’s Disease Neuroimaging Initiative*. Multiple imputation of covariates by fully conditional specification: accommodating the substantive model. Stat Methods Med Res. 2015; 24 ( 4 ): 462 - 487.; Wei LJ, Ying Z, Lin DY. Linear regression analysis of censored survival data based on rank tests. Biometrika. 1990; 77 ( 4 ): 845 - 851.; Jin Z, Lin DY, Wei LJ, Ying Z. Rank-based inference for the accelerated failure time model. Biometrika. 2003; 90 ( 2 ): 341 - 353.; Jin Z, Lin DY, Ying Z. Rank regression analysis of multivariate failure time data based on marginal linear models. Scand J Stat. 2006; 33 ( 1 ): 1 - 23.; Jin Z, Lin DY, Ying Z. On least-squares regression with censored data. Biometrika. 2006; 93 ( 1 ): 147 - 161.; Chiou SH, Kang S, Kim J, Yan J. Marginal semiparametric multivariate accelerated failure time model with generalized estimating equations. Lifetime Data Anal. 2014; 20 ( 4 ): 599 - 618.; Prentice RL, Zhao S. Nonparametric estimation of the multivariate survivor function: the multivariate Kaplan–Meier estimator. Lifetime Data Anal. 2018; 24 ( 1 ): 3 - 27.; Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc. 1958; 53 ( 282 ): 457 - 481.; Dabrowska DM. Kaplan-Meier estimate on the plane. Ann Stat. 1988; 16 ( 4 ): 1475 - 1489.; Nan B, Wellner JA. A general semiparametric Z-estimation approach for case-cohort studies. Stat Sin. 2013; 23 ( 3 ): 1155.; Kim SS, Meeker JD, Keil AP, et al. Exposure to 17 trace metals in pregnancy and associations with urinary oxidative stress biomarkers. Environ Res. 2019; 179: 108854.

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