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On goodness-of-fit of logistic regre...

Liu, Ying.

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On goodness-of-fit of logistic regression model.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	On goodness-of-fit of logistic regression model./
Author:	Liu, Ying.
Description:	130 p.
Notes:	Adviser: Shie-Shien Yang.
Contained By:	Dissertation Abstracts International69-03B.
Subject:	Statistics. -
ISBN:	9780549501213

On goodness-of-fit of logistic regression model.
Liu, Ying.

On goodness-of-fit of logistic regression model. - 130 p.

Adviser: Shie-Shien Yang.

Thesis (Ph.D.)--Kansas State University, 2007.

Logistic regression model is a branch of the generalized linear models and is widely used in many areas of scientific research. The logit link function and the binary dependent variable of interest make the logistic regression model distinct from linear regression model.

ISBN: 9780549501213Subjects--Topical Terms:

517247
Statistics.

On goodness-of-fit of logistic regression model.
LDR:02700nam 2200325 a 45 001 949558
005 20110525
008 110525s2007 ||||||||||||||||| ||eng d
020 $a 9780549501213
035 $a (UMI)AAI3304555
035 $a AAI3304555
040 $a UMI $c UMI
100 1 $a Liu, Ying. $3 898465
245 1 0 $a On goodness-of-fit of logistic regression model.
300 $a 130 p.
500 $a Adviser: Shie-Shien Yang.
500 $a Source: Dissertation Abstracts International, Volume: 69-03, Section: B, page: 1718.
502 $a Thesis (Ph.D.)--Kansas State University, 2007.
520 $a Logistic regression model is a branch of the generalized linear models and is widely used in many areas of scientific research. The logit link function and the binary dependent variable of interest make the logistic regression model distinct from linear regression model.
520 $a The conclusion drawn from a fitted logistic regression model could be incorrect or misleading when the covariates can not explain and/or predict the response variable accurately based on the fitted model---that is, lack-of-fit is present in the fitted logistic regression model.
520 $a The current goodness-of-fit tests can be roughly categorized into four types. (1) The tests are based on covariate patterns, e.g., Pearson's Chi-square test, Deviance D test, and Osius and Rojek's normal approximation test. (2) Hosmer-Lemeshow's C and Hosmer-Lemeshow's H tests are based on the estimated probabilities. (3) Score tests are based on the comparison of two models, where the assumed logistic regression model is embedded into a more general parametric family of models, e.g., Stukel's Score test and Tsiatis's test. (4) Smoothed residual tests include le Cessie and van Howelingen's test and Hosmer and Lemeshow's test. All of them have advantages and disadvantages.
520 $a In this dissertation, we proposed a partition logistic regression model which can be viewed as a generalized logistic regression model, since it includes the logistic regression model as a special case. This partition model is used to construct goodness-of-fit test for a logistic regression model which can also identify the nature of lack-of-fit is due to the tail or middle part of the probabilities of success. Several simulation results showed that the proposed test performs as well as or better than many of the known tests.
590 $a School code: 0100.
650 4 $a Statistics. $3 517247
690 $a 0463
710 2 $a Kansas State University. $b Department of Statistics. $3 1272944
773 0 $t Dissertation Abstracts International $g 69-03B.
790 $a 0100
790 1 0 $a Brown, Sue $e committee member
790 1 0 $a Nelson, Paul $e committee member
790 1 0 $a Wang, Hiayan $e committee member
790 1 0 $a Yang, Shie-Shien, $e advisor
791 $a Ph.D.
792 $a 2007