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EFFECTS OF MISSPECIFYING AN EXPLANATORY VARIABLE ON COEFFICIENTS OF DETERMINATION IN LOGISTIC REGRESSION
Author(s) -
Suay Ereeş,
Aylin Alın
Publication year - 2014
Publication title -
anadolu üniversitesi bilim ve teknoloji dergisi - b teorik bilimler
Language(s) - English
Resource type - Journals
eISSN - 2146-0191
pISSN - 2146-0272
DOI - 10.20290/btdb.14728
Subject(s) - logistic regression , statistics , mathematics , linear regression , cross sectional regression , variable (mathematics) , econometrics , regression analysis , regression diagnostic , polynomial regression , mathematical analysis
Normal 0 21 false false false TR X-NONE X-NONE Misspecifying an explanatory variable is a common problem in logistic regression as it is for all members of generalized linear models. Categorizing a continuous explanatory variable, using wrong functional form of an explanatory variable and omitting an explanatory variable from the model are commonly made misspecifications in logistic regression analysis. Studies show that all of these cases cause a loss in efficiency for test statistics. In this paper, the effects of these types of misspecification on asymptotic relative efficiency of different coefficients of determination are investigated. All calculations and comparisons are based on extensive simulation study using bootstrap methods /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Normal Tablo"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0cm; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;}

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