Journal ArticleDOI
New prediction method for the mixed logistic model applied in a marketing problem
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TLDR
A new methodology is proposed based on linear regression that considers the relationship among the random effects and the covariates aggregated at the group level, and indicates that LRPM drastically reduced the computational effort, and at the same time, maintained a similar level of prediction in relation to EBP.About:
This article is published in Computational Statistics & Data Analysis.The article was published on 2013-10-01. It has received 12 citations till now. The article focuses on the topics: Random effects model & Generalized linear mixed model.read more
Citations
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Journal ArticleDOI
Small area estimation of poverty proportions under area-level time models
TL;DR: The problem of estimating small area non linear parameters is treated, with special emphasis on the estimation of poverty proportions, and borrowing strength from time by using area-level linear time models is proposed.
Journal ArticleDOI
How to determine an optimal threshold to classify real-time crash-prone traffic conditions?
TL;DR: This method can be well-behaved to automatically identify thresholds in crash prediction, by minimizing the cross entropy between the original dataset with continuous probability of a crash occurring and the binarized dataset after using the thresholds to separate potential crash warnings against normal traffic conditions.
Journal ArticleDOI
A new class of semi-mixed effects models and its application in small area estimation
TL;DR: This class of semi-mixed effects models constitutes a continuum of models, indexed by a ''slider'', that determines the position of the model between these two extremes, so that the model selected can be close to the parsimonious random effects case, but far enough away from it to filter out unwanted dependences.
Journal Article
Predicción de quiebras empresariales en economías emergentes: uso de un modelo logístico mixto || Bankruptcy Prediction in Emerging Economies: Use of a Mixed Logistic Model
TL;DR: In this article, a replication and adaptation of Jones and Hensher (2004) model in an emerging economy with the purpose of testing its eternal validity is presented, and the main contribution of this new methodology is the important reduction of error type I to the 9 %.
Journal ArticleDOI
On the Predictive Properties of Binary Link Functions
Necla Gunduz,Ernest Fokoué +1 more
TL;DR: It turns out that not only are probit and logit perfectly predictively concordant, but the other link functions like cauchit and complementary log log enjoy very high percentage of predictive equivalence.
References
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Book
Applied Logistic Regression
David W. Hosmer,Stanley Lemeshow +1 more
TL;DR: Hosmer and Lemeshow as discussed by the authors provide an accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets.
Book
Hierarchical Linear Models: Applications and Data Analysis Methods
TL;DR: The Logic of Hierarchical Linear Models (LMLM) as discussed by the authors is a general framework for estimating and hypothesis testing for hierarchical linear models, and it has been used in many applications.
Journal ArticleDOI
Hierarchical Linear Models: Applications and Data Analysis Methods.
TL;DR: This chapter discusses Hierarchical Linear Models in Applications, Applications in Organizational Research, and Applications in the Study of Individual Change Applications in Meta-Analysis and Other Cases Where Level-1 Variances are Known.
Book
Practical Nonparametric Statistics
TL;DR: Probability Theory. Statistical Inference. Contingency Tables. Appendix Tables. Answers to Odd-Numbered Exercises and Answers to Answers to Answer Questions as discussed by the authors.