Polychotomous logistic model with missing values

被引：0

作者：

Karimlou, M.

Jandaghi, Gh. ^{[1
]}

Azam, K. ^{[2
]}

Grami, A. ^{[1
]}

Mohammad, K. ^{[2
]}

机构：

[1] Univ Tehran, Tehran 14174, Iran

[2] Univ Tehran Med Sci, Dept Epidemiol & Biostat, Tehran, Iran

来源：

SCIENTIFIC RESEARCH AND ESSAYS | 2009年 / 4卷 / 12期

关键词：

Missing at random; logistic regression; polychotomous response; goiter disease; likelihood function; MAXIMUM-LIKELIHOOD ESTIMATION; REGRESSION-MODELS;

D O I：

暂无

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

In health studies, we often face some variable missing. This missingness can happen in either response or other covariates. In this paper, the discussion focuses on missing covariates. A method is proposed for analysis of logistic regression models in which the response variable is polychotomous and some covariates' values are missing at random. The maximum likelihood function of the model is derived and the results are compared with the routine methods based on elimination of missing cases. Both the proposed method and the usual method are compared on a real dataset of goiter disease and is shown that the proposed method acts significantly better than usual method.

引用

页码：1463 / 1467

页数：5

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