Logistic Regression Diagnostics

Pregibon, Daryl

doi:10.1214/aos/1176345513

Cited by 1,079 publications

(568 citation statements)

References 11 publications

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“…Pregibon (1981) affirmed that the estimated LR correlation may be extremely influenced by outliers. Dealing with outliers necessitates the use of robust logistic regression models to overcome their influence on the LR model.…”

Section: Robust Logistic Regressionmentioning

confidence: 86%

“…Dealing with outliers necessitates the use of robust logistic regression models to overcome their influence on the LR model. Researches in this direction have been conducted by Hubert (1973), Pregibon (1981), Rousseeuw et Al. (1987), Yohai (1987), Copas (1988) and Rousseeuw (2003).…”

Section: Robust Logistic Regressionmentioning

confidence: 99%

“…Attention has been paid to the robust logistic regression, which is an area where outliers may also appear. Pregibon (1981) started by developing an analytical measure to assist in the detection of outliers and leverage points and quantify their effect on diverse aspects of the maximum likelihood fit. Thereafter, a good number of robust estimation procedures in the context of logistic regression have been examined.…”

Section: Introductionmentioning

confidence: 99%

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Self-Selecting Robust Logistic Regression Model

Gbohounme¹,

Ngesa²,

Eggoh³

2017

IJSP

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Logistic regression model is the most common model used for the analysis of binary data. However, the problem of atypical observations in the data has an unduly effect on the parameter estimates. Many researchers have developed robust statistical model to solve this problem of outliers. Gelman (2004) proposed GRLR, a robust model by trimming the probability of success in LR. The trimming values in this model were fixed and the user is required to specify this value well in advance. In particular this study developed SsRLR model by allowing the data itself to select the alpha value. We proposed a Restricted LR model to substitute the LR in presence of outliers. We proved that the SsRLR model is the more robust to the presence of leverage points in the data. Parameter estimations is done using a full Bayesian approach implemented in WinBUGS 14 software.

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Section: Robust Logistic Regressionmentioning

confidence: 86%

Section: Robust Logistic Regressionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Self-Selecting Robust Logistic Regression Model

Gbohounme¹,

Ngesa²,

Eggoh³

2017

IJSP

View full text Add to dashboard Cite

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“…If we focus on the analysis of the logistic model, fairly abundant tools for the diagnoses have been developed (Pregibon, 1981 ;Schoenfeld, 1982;Landwehr et al, 1984). We briefly mention these tools for diagnosis about the model (2) based on the APT.…”

Section: Resultsmentioning

confidence: 99%

“…In the analysis of nonlinear models, it is difficult to descern if these outliers are those on the response variable or those on the explanatory variables. Pregibon (1981) has proposed some plotting methods to find out influence of a case on overall goodness of fit by eliminating the case. Dempster et al (1981) have examined a method to allocate p-value to all cases, by arranging them in increasing order of the badness of fit, in the case of linear regression.…”

Section: Resultsmentioning

confidence: 99%

Power-Transformation for Ordered Categorical Data

1986

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We consider in this paper a model of asymmetric power-transformation of response probability explained by linear function of some covariates. This model includes logistic and complementary log-log transformation models as its specific case, so we can use the model to evaluate the appropriateness or the goodness of fit of these models. Then the performances of the asymmetric power-transformation model are evaluated and examined, based on data used in published literatures.And we discuss various issues of diagnoses which may occur in the process of applying the model. Further we consider alternative transformations, and then in comparison with them, we point out the advantages of the asymmetric power-transformation.

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Nasopharyngeal carcinoma in Malaysian Chinese: Salted fish and other dietary exposures

et al. 1998

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We interviewed 282 histologically confirmed cases of nasopharyngeal carcinoma (NPC) in Chinese residents of Selangor and the Federal Territory, Malaysia, and an equal number of Chinese age‐, sex‐, and length‐of‐residence‐matched controls sampled from the general population. Consumption of 55 dietary items during childhood, and 5 years pre‐diagnosis of NPC, was analyzed by univariate and multivariate methods. Four salted preserved foods (fish, leafy vegetables, egg and root), fresh pork/beef organ meats and beer and liquor consumption exhibited strong positive associations, and 4 vegetable/fruit combinations strong negative associations with NPC. Factor analysis and multivariable modeling using estimated factor scores strongly supported separate effects on NPC of vegetables/fruits, salted preserved foods, pork/beef organ meats and beer/liquor consumption. Multivariable modeling associated NPC most clearly with high consumption of salted fish, salted eggs, pork/beef liver and beer and low consumption of Chinese flowering cabbage, oranges/tangerines and shrimp. A strong residual association of social class with NPC remained after adjustment for diet, which is consistent with a substantial role for non‐dietary environmental factors. Int. J. Cancer 77:228–235, 1998.© 1998 Wiley‐Liss, Inc.

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Logistic Regression Diagnostics

Cited by 1,079 publications

References 11 publications

Self-Selecting Robust Logistic Regression Model

Self-Selecting Robust Logistic Regression Model

Power-Transformation for Ordered Categorical Data

Nasopharyngeal carcinoma in Malaysian Chinese: Salted fish and other dietary exposures

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