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New regression models to data set with binary and/or bounded response

Grant number: 17/15452-5
Support type:Scholarships abroad - Research
Effective date (Start): March 01, 2018
Effective date (End): February 28, 2019
Field of knowledge:Physical Sciences and Mathematics - Probability and Statistics
Principal Investigator:Jorge Luis Bazan Guzman
Grantee:Jorge Luis Bazan Guzman
Host: Dipak Kumar Dey
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Local de pesquisa : University of Connecticut (UCONN), United States  

Abstract

The main objective of this project is to propose different regression models for binary and/orlimited responses in the unit interval studying aspects of inference and modeling when consideredreal data. Specifically, the project aims to develop new regression models to the case of discrete limited responses in the unit interval considering by example proposals of new links for binary regression models. Besides that, we studied the case of new regression models to continuouslimited response. Extensions this models to ordinal regression model, mixed regression modeland item response theory are also considered. . Simulation and application studies to real data complete the objectives of this project. The proposal is justified by the shortage of research that accommodates such kind of data, the practical implications of the results of such modeling, by the relevance of the working together with Prof. Dipak Dey and to reinforce the contact with the Department of Statistics at the University Of Connecticut. It is expected publish paper in relevant international journals, made presentations in scientific meetings in order to disseminate the results obtained as well as the institutions involved. Likewise, it is hoped the reinforce of the partnership between the two universities, with the aim of establishing new projects including the participation of graduate students.

Scientific publications (4)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
DA PAZ, ROSINEIDE F.; BALAKRISHNAN, NARAYANASWAMY; BAZAN, JORGE LUIS. L-Logistic regression models: Prior sensitivity analysis, robustness to outliers and applications. BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS, v. 33, n. 3, p. 455-479, AUG 2019. Web of Science Citations: 0.
DA SILVA, MARCELO A.; LIU, REN; HUGGINS-MANLEY, ANNE C.; BAZAN, JORGE L. Incorporating the Q-Matrix Into Multidimensional Item Response Theory Models. EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT, v. 79, n. 4, p. 665-687, AUG 2019. Web of Science Citations: 0.
HUAYANAY, ALEX DE LA CRUZ; BAZAN, JORGE L.; CANCHO, VICENTE G.; DEY, DIPAK K. Performance of asymmetric links and correction methods for imbalanced data in binary regression. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, v. 89, n. 9, p. 1694-1714, JUN 13 2019. Web of Science Citations: 0.
DA SILVA, MARCELO A.; HUGGINS-MANLEY, ANNE C.; MAZZON, JOSE A.; BAZAN, JORGE L. Bayesian estimation of a flexible bifactor generalized partial credit model to survey data. Journal of Applied Statistics, v. 46, n. 13, p. 1-16, MAR 2019. Web of Science Citations: 0.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.