Checking the adequacy of partial linear models with missing covariates at random

Wangli Xu, Xu Guo

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In this paper, we consider the goodness-of-fit for checking whether the nonparametric function in a partial linear regression model with missing covariate at random is a parametric one or not. We estimate the selection probability by using parametric and nonparametric approaches. Two score type tests are constructed with the estimated selection probability. The asymptotic distributions of the test statistics are investigated under the null and local alterative hypothesis. Simulation studies are carried out to examine the finite sample performance of the sizes and powers of the tests. We apply the proposed procedure to a data set on the AIDS clinical trial group (ACTG 315) study.

Original languageEnglish (US)
Pages (from-to)473-490
Number of pages18
JournalAnnals of the Institute of Statistical Mathematics
Volume65
Issue number3
DOIs
StatePublished - Jun 1 2013

Fingerprint

Partial Linear Model
Missing Covariates
Goodness of fit
Linear Regression Model
Clinical Trials
Asymptotic distribution
Test Statistic
Null
Simulation Study
Partial
Estimate

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

Cite this

@article{f60c127ea64e4b4b801f7e8015c42152,
title = "Checking the adequacy of partial linear models with missing covariates at random",
abstract = "In this paper, we consider the goodness-of-fit for checking whether the nonparametric function in a partial linear regression model with missing covariate at random is a parametric one or not. We estimate the selection probability by using parametric and nonparametric approaches. Two score type tests are constructed with the estimated selection probability. The asymptotic distributions of the test statistics are investigated under the null and local alterative hypothesis. Simulation studies are carried out to examine the finite sample performance of the sizes and powers of the tests. We apply the proposed procedure to a data set on the AIDS clinical trial group (ACTG 315) study.",
author = "Wangli Xu and Xu Guo",
year = "2013",
month = "6",
day = "1",
doi = "10.1007/s10463-012-0379-4",
language = "English (US)",
volume = "65",
pages = "473--490",
journal = "Annals of the Institute of Statistical Mathematics",
issn = "0020-3157",
publisher = "Springer Netherlands",
number = "3",

}

Checking the adequacy of partial linear models with missing covariates at random. / Xu, Wangli; Guo, Xu.

In: Annals of the Institute of Statistical Mathematics, Vol. 65, No. 3, 01.06.2013, p. 473-490.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Checking the adequacy of partial linear models with missing covariates at random

AU - Xu, Wangli

AU - Guo, Xu

PY - 2013/6/1

Y1 - 2013/6/1

N2 - In this paper, we consider the goodness-of-fit for checking whether the nonparametric function in a partial linear regression model with missing covariate at random is a parametric one or not. We estimate the selection probability by using parametric and nonparametric approaches. Two score type tests are constructed with the estimated selection probability. The asymptotic distributions of the test statistics are investigated under the null and local alterative hypothesis. Simulation studies are carried out to examine the finite sample performance of the sizes and powers of the tests. We apply the proposed procedure to a data set on the AIDS clinical trial group (ACTG 315) study.

AB - In this paper, we consider the goodness-of-fit for checking whether the nonparametric function in a partial linear regression model with missing covariate at random is a parametric one or not. We estimate the selection probability by using parametric and nonparametric approaches. Two score type tests are constructed with the estimated selection probability. The asymptotic distributions of the test statistics are investigated under the null and local alterative hypothesis. Simulation studies are carried out to examine the finite sample performance of the sizes and powers of the tests. We apply the proposed procedure to a data set on the AIDS clinical trial group (ACTG 315) study.

UR - http://www.scopus.com/inward/record.url?scp=84878524184&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84878524184&partnerID=8YFLogxK

U2 - 10.1007/s10463-012-0379-4

DO - 10.1007/s10463-012-0379-4

M3 - Article

VL - 65

SP - 473

EP - 490

JO - Annals of the Institute of Statistical Mathematics

JF - Annals of the Institute of Statistical Mathematics

SN - 0020-3157

IS - 3

ER -