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| Cui, James. |
| The generalized estimating equation (GEE) approach is a widely used statistical method in the analysis of longitudinal data in clinical and epidemiological studies. It is an extension of the generalized linear model (GLM) method to correlated data such that valid standard errors of the parameter estimates can be drawn. Unlike the GLM method, which is based on the maximum likelihood theory for independent observations, the GEE method is based on the quasilikelihood theory and no assumption is made about the distribution of response observations. Therefore, Akaike’s information criterion, a widely used method for model selection in GLM, is not applicable to GEE directly. However, Pan (Biometrics 2001; 57: 120–125) proposed a model-selection method for GEE... |
| Tipo: Article |
Palavras-chave: Qic; Akaike's information criterion; GEE; Likelihood; Model; Quasilikelihood under the independence model criterion; Research Methods/ Statistical Methods. |
| Ano: 2007 |
URL: http://purl.umn.edu/119269 |
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| Cui, James. |
| The Buckley–James method and the Cox proportional hazards model were proposed in the 1970s. Both methods can be used to analyze survival-type data, although the former focuses on calculation of the expected value of the survival time and the latter on the relative risk of explanatory variables on the failure event. In cardiovascular disease epidemiological studies, it is essential to correct the effect of taking antihypertensive medicine, which means we need to calculate the expected blood pressure for people who take the medicine. I developed a Stata program to calculate the Buckley–James estimate. I will describe how to use this program to calculate the expected value of a censored outcome and illustrate the method through an example from a... |
| Tipo: Journal Article |
Palavras-chave: Buckley–James method; Censoring; Expectation; Survival; Research Methods/ Statistical Methods. |
| Ano: 2005 |
URL: http://purl.umn.edu/117542 |
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