127
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

Regression with incomplete multivariate surrogate responses for a latent covariate

ORCID Icon & ORCID Icon
Pages 247-264 | Received 13 Nov 2019, Accepted 03 May 2020, Published online: 29 Jul 2020

References

  • Grove W, Andreasen N, McDonald-Scott P, et al. Reliability studies of psychiatric diagnosis: theory and practice. Arch Gen Psychiatry. 1981;38(4):408–413. doi: 10.1001/archpsyc.1981.01780290042004
  • Perrot S, Choy E, Petersel D, et al. Survey of physician experiences and perceptions about the diagnosis and treatment of fibromyalgia. BMC Health Serv Res. 2012;12(356):160.
  • Meade M, Guyatt G, Cook R, et al. Agreement between alternative classifications of acute respiratory distress syndrome. Am J Respir Crit Care Med. 2001;163(2):490–493. doi: 10.1164/ajrccm.163.2.2006067
  • Gustafson P. Measurement error and misclassification in statistics and epidemiology: impacts and Bayesian adjustments. Boca Raton: CRC Press; 2003.
  • Carroll R, Ruppert D, Crainiceanu C, et al. Measurement error in nonlinear models: a modern perspective. Boca Raton: Chapman and Hall/CRC; 2006.
  • Buonaccorsi J. Measurement error: models, methods, and applications. Boca Raton: CRC Press; 2010.
  • Yi G. Statistical analysis with measurement error or misclassification. New York: Springer; 2016.
  • Greenland S. Variance estimation for epidemiologic effect estimates under misclassification. Stat Med. 1988;7(7):745–757. doi: 10.1002/sim.4780070704
  • Marshall R. Validation study methods for estimating exposure proportions and odds ratios with misclassified data. J Clin Epidemiol. 1990;43(9):941–947. doi: 10.1016/0895-4356(90)90077-3
  • Holcroft C, Spiegelman D. Design of validation studies for estimating the odds ratio of exposure-disease relationships when exposure is misclassified. Biometrics. 1999;55(4):1193–1201. doi: 10.1111/j.0006-341X.1999.01193.x
  • Morrissey M, Spiegelman D. Matrix methods for estimating odds ratios with misclassified exposure data: extensions and comparisons. Biometrics. 1999;55(2):338–344. doi: 10.1111/j.0006-341X.1999.00338.x
  • Spiegelman D, Rosner B, Logan R. Estimation and inference for logistic regression with covariate misclassification and measurement error in main study/validation study designs. J Am Stat Assoc. 2000;95(449):51–61. doi: 10.1080/01621459.2000.10473898
  • Rindskopf D, Rindskopf W. The value of latent class analysis in medical diagnosis. Stat Med. 1986;5(1):21–27. doi: 10.1002/sim.4780050105
  • Liu X, Liang KY. Adjustment for non-differential misclassification error in the generalized linear model. Stat Med. 1991;10(8):1197–1211. doi: 10.1002/sim.4780100804
  • Chu H, Cole SR, Wei Y, et al. Estimation and inference for case-control studies with multiple non-gold standard exposure assessments: with an occupational health application. Biostatistics. 2009;10(4):591–602. doi: 10.1093/biostatistics/kxp015
  • Yi G, He W. Analysis of case-control data with interacting misclassified covariates. J Stat Distrib Appl. 2017;4(16):1151.
  • Dempster A, Laird N, Rubin D. Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B (Methodol). 1977;39(1):1–22.
  • Louis T. Finding the observed information matrix when using the EM algorithm. J Royal Stat Soc: Ser B (Methodol). 1982;44(2):226–233.
  • Walter S, Irwig L. Estimation of test error rates, disease prevalence and relative risk from misclassified data: a review. J Clin Epidemiol. 1988;41(9):923–937. doi: 10.1016/0895-4356(88)90110-2
  • Shih J, Louis T. Inferences on the association parameter in copula models for bivariate survival data. Biometrics. 1995;51(4):1384–1399. doi: 10.2307/2533269
  • Rubin DB. Inference and missing data. Biometrika. 1976;63(3):581–592. doi: 10.1093/biomet/63.3.581
  • Feng X, Li H, Dean M, et al. Low ATM protein expression in malignant tumor as well as cancer-associated stroma are independent prognostic factors in a retrospective study of early-stage hormone-negative breast cancer. Breast Cancer Res. 2015;17(65):2817.
  • Feng X, Li H, Kornaga E, et al. Low Ki67/high ATM protein expression in malignant tumors predicts favorable prognosis in a retrospective study of early stage hormone receptor positive breast cancer. Oncotarget. 2016;7(52):85798–85812. doi: 10.18632/oncotarget.12622
  • Camp R, Dolled-Filhart M, Rimm D. X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization. Clin Cancer Res. 2004;10(21):7252–7259. doi: 10.1158/1078-0432.CCR-04-0713
  • Reilly M, Pepe MS. A mean score method for missing and auxiliary covariate data in regression models. Biometrika. 1995;82(2):299–314. doi: 10.1093/biomet/82.2.299
  • Rotnitzky A, Robins JM, Scharfstein DO. Semiparametric regression for repeated outcomes with nonignorable nonresponse. J Am Stat Assoc. 1998;93(444):1321–1339. doi: 10.1080/01621459.1998.10473795
  • Bang H, Robins JM. Doubly robust estimation in missing data and causal inference models. Biometrics. 2005;61(4):962–973. doi: 10.1111/j.1541-0420.2005.00377.x
  • Schafer JL. Multiple imputation: a primer. Stat Methods Med Res. 1999;8(1):3–15. doi: 10.1177/096228029900800102

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.