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# Simulation-based estimation in regression models with categorical response variable and mismeasured covariates

 dc.contributor.supervisor Wang, Liqun (Statistics) en_US Martsynyuk, Yuliya (Statistics) dc.contributor.author Haddadian, Rojiar dc.date.accessioned 2016-07-27T19:24:36Z dc.date.available 2016-07-27T19:24:36Z dc.date.issued 2016 dc.identifier.uri http://hdl.handle.net/1993/31535 dc.description.abstract A common problem in regression analysis is that some covariates are measured with errors. In this dissertation we present simulation-based approach to estimation in two popular regression models with a categorical response variable and classical measurement errors in covariates. The first model is the regression model with a binary response variable. The second one is the proportional odds regression with an ordinal response variable. en_US In both regression models we consider method of moments estimators for therein unknown parameters that are defined via minimizing respective objective functions. The later functions involve multiple integrals and make obtaining of such estimators unfeasible. To overcome this computational difficulty, we propose Simulation-Based Estimators (SBE). This method does not require parametric assumptions for the distributions of the unobserved covariates and error components. We prove consistency and asymptotic normality of the proposed SBE's under some regularity conditions. We also examine the performance of the SBE's in finite-sample situations through simulation studies and two real data sets: the data set from the AIDS Clinical Trial Group (ACTG175) study for our logistic and probit regression models and one from the Adult Literacy and Life Skills (ALL) Survey for our regression model with the ordinal response variable and mismeasured covariates. dc.subject Cumulative logit model, Instrumental variables, Mea- surement error, Method of moments, Ordinal response, Probit model, Proportional odds model, Simulation-based estimation. en_US dc.title Simulation-based estimation in regression models with categorical response variable and mismeasured covariates en_US dc.degree.discipline Statistics en_US dc.contributor.examiningcommittee Wang, Xikui (Statistics) Torabi, Mahmoud (Community Health Sciences) en_US He, Wenqing (Statistical and actuarial Sciences) dc.degree.level Doctor of Philosophy (Ph.D.) en_US dc.description.note October 2016 en_US
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