Efficiency transfer for regression models with responses missing at random
نویسندگان
چکیده
منابع مشابه
Efficiency transfer for regression models with responses missing at random
We consider independent observations on a random pair (X,Y ), where the response Y is allowed to be missing at random but the covariate vector X is always observed. We demonstrate that characteristics of the conditional distribution of Y given X can be estimated efficiently using complete case analysis, i.e., one can simply omit incomplete cases and work with an appropriate efficient estimator ...
متن کاملMulti-index regression models with missing covariates at random
AMS subject classifications: 62H12 62G20 Keywords: Covariates missing at random Inverse selection probability Multi-index model Single-index model a b s t r a c t This paper considers estimation of the semiparametric multi-index model with missing covariates at random. A weighted estimating equation is suggested by invoking the inverse selection probability approach, and estimators of the indic...
متن کاملPartially linear varying coefficient models with missing at random responses
This paper considers partially linear varying coefficient models when the response variable is missing at random. The paper uses imputation techniques to develop an omnibus specification test. The test is based on a simple modification of a Cramer von Mises functional that overcomes the curse of dimensionality often associated with the standard Cramer von Mises functional. The paper also consid...
متن کاملEmpirical likelihood semiparametric nonlinear regression analysis for longitudinal data with responses missing at random
This paper develops the empirical likelihood (EL) inference on parameters and baseline function in a semiparametric nonlinear regression model for longitudinal data in the presence of missing response variables. We propose two EL-based ratio statistics for regression coefficients by introducing the working covariance matrix and a residual-adjusted EL ratio statistic for baseline function. We es...
متن کاملSieve Maximum Likelihood Estimation for Regression Models With Covariates Missing at Random
Missing covariates are common in regression problems. We propose a new semiparametric method based on a fully nonparametric distribution for the missing covariates that are assumed to be missing at random. The method of sieve maximum likelihood estimation is used to obtain the estimators of the regression coefficients. These estimators are shown to be consistent and asymptotically normal with t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bernoulli
سال: 2017
ISSN: 1350-7265
DOI: 10.3150/16-bej824