![]() To access the DECLARATION AND TRANSFER OF COPYRIGHT AUTHOR’S DECLARATION AND COPYRIGHT LICENSE click here.Įthical Guidelines for Journal Publication Em: International Biometrics Conference, pp. Logit models and logistic regressions for social networks: I. Transactions of the American Mathematical Society, 64, 426–482. Tests of statistical hypotheses concerning several parameters when the number of observations is large. Computational Statistics and Data Analysis, 74, 110–124. Improved likelihood inference in generalized linear models. Electronic Journal of Statistics, 7, 43–61. Gradient statistic: Higher-order asymptotics and Bartletttype correction. Computing Science and Statistics, 34, 206–215. Mathematical Proceedings of the Cambridge Philosophical Society, 44(01), 50–57. Large sample tests of statistical hypotheses concerning several parameters with applications to problems of estimation. Journal of the Royal Statistical Society, Vol. Tests for specification errorsin classical linear least-squares regression analysis. ![]() Oxford bulletin of economics and statistics, 74, 107–130. Alternative versions of the reset test for binary response index models: A comparative study. R Foundation for Statistical Computing, Vienna, Austria, ISBN 3-900051- 07-0. R: A Language and Environment for Statistical Computing. Communications in Statistics - Simulation and Computation, 43, 631–656. Detecting model misspecification in inflated beta regressions. Modelos de Regressão com Apoio Computacional. Dissertação de Mestrado, Universidade Federal de Pernanbuco. Detectando má especificação em regressão beta. On the use and interpretation of certain test criteria for purposes of statistical inference. Journal of the Royal Statistical Society Series A, 135, 370–384. Local power and size properties of the lr, wald, score and gradient testsin dispersion models. On the gradient statistic under model misspecification. Parametric links for binary choice models: A fisherian-bayesian colloquy. Transformation diagnostics for linear models. Tutorial in biostatistics multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Modelos Lineares Generalizados em Experimentação Agronômica. Minicurso para o 12o SEAGRO e a 52ª Reunião Anual da RBRAS UFSM, Santa Maria, RS.ĭemétrio, C. Journal of Econometrics, 76, 323–340.Ĭordeiro, G. Semi-nonparametric estimation of binary response models with an application to natural resource valuation. The likelihood ratio, wald and lagrange multiplier tests: An expository note. Journal of Statistical Planning and Inference, 143, 531–547.īuse, A. Bartlett corrections in beta regression models. The application of gisbased logistic regression for landslide susceptibility mapping in the kakuda-yahiko mountains, central japan. ![]() Dissertação de Mestrado, Universidade Federal de São Paulo.Īyalew, L., Yamagishi, H. Efeitos da especificação incorreta da função de ligação no modelo de regressão beta. IEEE Transactions on Automatic Control, 19(6), 716–726.Īndrade, A. A new look at the statistical model identification. An empirical application to a real data set is considered for illustrative purposes.Īkaike, H. The gradient statistic outperforms the traditional statistics, especially in smaller sample sizes. ![]() It can be seen that the performance of the tests are influenced by the used link function and the sample size. The finite sample performance of the tests were evaluated in terms of size and power tests. The performance evaluation of misspecification tests were performed using Monte Carlo simulations. To perform the RESET test we consider the likelihood ratio, Wald and score traditional statistics and we propose the use of the emerging gradient statistic. This paper addresses the issue of check the correct specification of the link function in generalized linear models for binary data.
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