Martingale model diagnostic for assessing the fit of logistic regression model to recurrent events data are studied. One way of assessing the fit is by plotting the empirical standard deviation of the standardized martingale residual processes. Here we used another diagnostic plot based on martingale residual covariance. We investigated the plot performance under several types of model misspecification. Clearly the method has correctly picked up the wrong model. Also we present a test statistic that supplement the inspection of the two diagnostic. The test statistic power agrees with what we have seen in the plots of the estimated martingale covariance
In this article, we compare three residuals based on the deviance component in generalised log-gamma...
Abstract: We examine the residual-based diagnostics for univariate and multivari-ate conditional het...
This paper presents a new class of graphical and numerical methods for checking the adequacy of the ...
One method of assessing the fit of an event history model is to plot the empirical standard deviatio...
Residual analysis is used commonly in statistical tests of model fit, i.e. of good correspondence be...
This paper considers residuals for time series regression. Despite much literature on visual diagnos...
This paper presents a new class of graphical and numerical methods for checking the adequacy of the ...
In logistic regression, before concluding that the model fits well, it is crucial that other measure...
Standard use of Cox's regression model and other relative risk regression models for censored surviv...
In this article, we derive the asymptotic distribution of residual autocovariance and autocorrelatio...
In this paper, we compare three residuals to assess departures from the error assumptions as well as...
International audienceThe use of martingale residuals have been proposed for model checking and also...
The martingale hypothesis is commonly tested in financial and economic time series. The existing tes...
Logistic regression is one of the most frequently used statistical methods as a standard method of d...
Traditional tools for model diagnosis for Generalized Linear Model (GLM), such as deviance and Pears...
In this article, we compare three residuals based on the deviance component in generalised log-gamma...
Abstract: We examine the residual-based diagnostics for univariate and multivari-ate conditional het...
This paper presents a new class of graphical and numerical methods for checking the adequacy of the ...
One method of assessing the fit of an event history model is to plot the empirical standard deviatio...
Residual analysis is used commonly in statistical tests of model fit, i.e. of good correspondence be...
This paper considers residuals for time series regression. Despite much literature on visual diagnos...
This paper presents a new class of graphical and numerical methods for checking the adequacy of the ...
In logistic regression, before concluding that the model fits well, it is crucial that other measure...
Standard use of Cox's regression model and other relative risk regression models for censored surviv...
In this article, we derive the asymptotic distribution of residual autocovariance and autocorrelatio...
In this paper, we compare three residuals to assess departures from the error assumptions as well as...
International audienceThe use of martingale residuals have been proposed for model checking and also...
The martingale hypothesis is commonly tested in financial and economic time series. The existing tes...
Logistic regression is one of the most frequently used statistical methods as a standard method of d...
Traditional tools for model diagnosis for Generalized Linear Model (GLM), such as deviance and Pears...
In this article, we compare three residuals based on the deviance component in generalised log-gamma...
Abstract: We examine the residual-based diagnostics for univariate and multivari-ate conditional het...
This paper presents a new class of graphical and numerical methods for checking the adequacy of the ...