[[abstract]]This paper is emphasized on the logistic regression model fit with continuous and categorical covariates. A test statistic based on non-parametric local linear regression technique with optimal bandwidth which is chosen by cross validation method is proposed. This proposed test does not require a space partition of covariates or groups of the fitted values to compensate a small expected cell size. The expectation and variance of the proposed test statistic are computed and the sampling distributions of test statistic for various of logistic regression models are evaluated. We use simulations to compare the power of the new test with that of the current assessing methods for different logistic models. The proposed method is illus...
This thesis contributes to the development of test procedures for structured models (Chapters 2, 3 a...
In this note, we consider several goodness-of-fit tests for model specifica-tion in nonparametric re...
In the context of polytomous regression, as with any generalized linear model, robustness issues are...
[[abstract]]Logistic-normal models can be applied for analysis of longitudinal binary data. The aim ...
[[abstract]]A nonparametric local linear smoothing technique for testing goodness-of-fit of ordinal ...
[[abstract]]A new test is proposed for testing the validity of the logistic regression model based o...
Abstract: Local linear kernel methods have been shown to dominate local constant methods for the non...
In this paper we consider a nonparametric regression model which admits a mix of continuous and disc...
The smooth testing approach described in [2] has been used to develop a test of the distributional a...
A smooth testing approach has been used to develop a test of the distributional assumption for gener...
Abstract. In this paper we propose a test for the signicance of categorical predictors in nonparamet...
The problem of sample size estimation is important in medical applications, especially in cases of e...
The lognormal distribution has a very long history and is almost as important as its sister distribu...
Abstract In this note we consider several goodness-of-fit tests for model specification in nonparame...
Abstract. In this paper we propose a test for the signi¯cance of categorical predictors in nonparame...
This thesis contributes to the development of test procedures for structured models (Chapters 2, 3 a...
In this note, we consider several goodness-of-fit tests for model specifica-tion in nonparametric re...
In the context of polytomous regression, as with any generalized linear model, robustness issues are...
[[abstract]]Logistic-normal models can be applied for analysis of longitudinal binary data. The aim ...
[[abstract]]A nonparametric local linear smoothing technique for testing goodness-of-fit of ordinal ...
[[abstract]]A new test is proposed for testing the validity of the logistic regression model based o...
Abstract: Local linear kernel methods have been shown to dominate local constant methods for the non...
In this paper we consider a nonparametric regression model which admits a mix of continuous and disc...
The smooth testing approach described in [2] has been used to develop a test of the distributional a...
A smooth testing approach has been used to develop a test of the distributional assumption for gener...
Abstract. In this paper we propose a test for the signicance of categorical predictors in nonparamet...
The problem of sample size estimation is important in medical applications, especially in cases of e...
The lognormal distribution has a very long history and is almost as important as its sister distribu...
Abstract In this note we consider several goodness-of-fit tests for model specification in nonparame...
Abstract. In this paper we propose a test for the signi¯cance of categorical predictors in nonparame...
This thesis contributes to the development of test procedures for structured models (Chapters 2, 3 a...
In this note, we consider several goodness-of-fit tests for model specifica-tion in nonparametric re...
In the context of polytomous regression, as with any generalized linear model, robustness issues are...