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via multiclass *logistic* *regression* *modeling*

, 2013

"... Variable and boundary selection for functional data via multiclass logistic regression modeling ..."

Abstract
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Variable and boundary selection for functional data via multiclass

*logistic**regression**modeling*###
*Logistic* *Regression* *Model*

"... Abstract — The objective of this research involved the investigation of the empirical distribution of the statistics that were used to examine whether or not the logistic regression model fit the data when the sample size was small. These statistics were Wald, Score, Likelihood Ratio, Hosmer-Lemesho ..."

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Abstract — The objective of this research involved the investigation of the empirical distribution of the statistics that were used to examine whether or not the

*logistic**regression**model*fit the data when the sample size was small. These statistics were Wald, Score, Likelihood Ratio, Hosmer###
The Hidden *Logistic* *Regression* *Model*

, 2001

"... The logistic regression model is commonly used to describe the effect of one or several explanatory variables on a binary response variable. Here we consider an alternative model under which the observed response is strongly related but not equal to the unobservable true response. We call this the h ..."

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The

*logistic**regression**model*is commonly used to describe the effect of one or several explanatory variables on a binary response variable. Here we consider an alternative*model*under which the observed response is strongly related but not equal to the unobservable true response. We call###
The Extreme Residuals in *Logistic* *Regression* *Models*

, 1985

"... Goodness of fit tests for logistic regression models using extreme residuals are considered. Moment properties of the Pearson residuals are developed and used to define modified residuals, for the cases when the model fit is made by maximum likelihood, minimum chi-square and weighted l ..."

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Goodness of fit tests for

*logistic**regression**models*using extreme residuals are considered. Moment properties of the Pearson residuals are developed and used to define modified residuals, for the cases when the*model*fit is made by maximum likelihood, minimum chi-square and weighted###
*Logistic* *Regression* *Model*

"... • Consider a data set where the response variable takes only 0 or 1 values (e.g., Yes/No type, we code Yes = 1 and No = 0) and the single covariate variable is (continues) numerical type. [Insert Figure 2.1 for an example data] • If we apply a simple linear regression model yi = β0 + β1xi + ɛi to fi ..."

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• Consider a data set where the response variable takes only 0 or 1 values (e.g., Yes/No type, we code Yes = 1 and No = 0) and the single covariate variable is (continues) numerical type. [Insert Figure 2.1 for an example data] • If we apply a simple linear

*regression**model*yi = β0 + β1xi + ɛi###
*logistic* *regression* *models* with

, 2015

"... descent algorithms for nonconvex penalized linear and ..."

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*Logistic* *Regression* *Model* with Surrogate Covariate

"... this paper presents the logistic regression model with surrogate covariate and the three methods of estimation. In Section 3, a brief introduction is given to the empirical likelihood and it is shown, explicitly, how empirical likelihood can be applied to the present problem. Section 4 derives the a ..."

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this paper presents the

*logistic**regression**model*with surrogate covariate and the three methods of estimation. In Section 3, a brief introduction is given to the empirical likelihood and it is shown, explicitly, how empirical likelihood can be applied to the present problem. Section 4 derives###
APPLYING *LOGISTIC* *REGRESSION* *MODEL* TO THE EXAMINATION RESULTS DATA

"... The binary logistic regression model is used to analyze the school examination results (scores) of 1002 students. The analysis is performed on the basis of the independent variables viz. ..."

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The binary

*logistic**regression**model*is used to analyze the school examination results (scores) of 1002 students. The analysis is performed on the basis of the independent variables viz.###
Detecting Heterogeneity in *Logistic* *Regression* *Models*

"... In the context of item response theory, it is not uncommon that person-by-item data are correlated beyond the correlation that is captured by the model—in other words, there is extra binomial variation. Heterogeneity of the parameters can explain this variation. There is a need for proper statistica ..."

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In the context of item response theory, it is not uncommon that person-by-item data are correlated beyond the correlation that is captured by the

*model*—in other words, there is extra binomial variation. Heterogeneity of the parameters can explain this variation. There is a need for proper