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http://ir.library.ui.edu.ng/handle/123456789/5327
Title: | Alternative goodness-of-fit test in logistic regression models |
Authors: | Nja, M. E. Enang, E. I. Chukwu, A. U. Udomboso, C. G. |
Keywords: | Deviance Pearson chi-square Standard error Observed proportions Predicted probabilities p value Nigeria |
Issue Date: | 2011 |
Publisher: | Medwell Journals |
Abstract: | The Deviance and the Pearson chi-square are two traditional goodness-of-fit tests in generalized linear models for which the logistic model is a special case. The effort involved in the computation of either the Deviance or Pearson chi-square statistic is enormous and this provides a reason for prospecting an alternative goodness-of-fit test in logistic regression models with discrete predictor variables. The Deviance is based on the log likelihood function while the Pearson chi-square derives from the discrepancies between observed and predicted counts. Replacing observed and predicted counts with observed proportions and predicted probabilities, respectively in a cross-classification data arrangement, the standard error of estimate is proposed as an alternative goodness-of-fit test in logistic regression models. The illustrative example returns favourable comparisons with Deviance and the Pearson chi-square statistics. |
URI: | http://ir.library.ui.edu.ng/handle/123456789/5327 |
ISSN: | 1994-5388 |
Appears in Collections: | Scholarly works |
Files in This Item:
File | Description | Size | Format | |
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(14) ui_art_nja_alternative_2011.pdf | 485.26 kB | Adobe PDF | View/Open |
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