Quadratic inference functions in marginal models for longitudinal data with time-varying stochastic covariates
نویسندگان
چکیده
منابع مشابه
Quadratic inference functions in marginal models for longitudinal data.
The quadratic inference function (QIF) is a new statistical methodology developed for the estimation and inference in longitudinal data analysis using marginal models. This method is an alternative to the popular generalized estimating equations approach, and it has several useful properties such as robustness, a goodness-of-fit test and model selection. This paper presents an introductory revi...
متن کاملQuadratic inference functions for varying-coefficient models with longitudinal data.
Nonparametric smoothing methods are used to model longitudinal data, but the challenge remains to incorporate correlation into nonparametric estimation procedures. In this article, we propose an efficient estimation procedure for varying-coefficient models for longitudinal data. The proposed procedure can easily take into account correlation within subjects and deal directly with both continuou...
متن کاملRobust Inference for Time-Varying Coefficient Models with Longitudinal Data
Time-varying coefficient models are useful in longitudinal data analysis. Various efforts have been invested for the estimation of the coefficient functions, based on the least squares principle. Related work includes smoothing spline and kernel methods among others, but these methods suffer from the shortcoming of non-robustness. In this paper, we introduce a local M-estimation method for esti...
متن کاملMarginal modeling of multilevel binary data with time-varying covariates.
We propose and compare two approaches for regression analysis of multilevel binary data when clusters are not necessarily nested: a GEE method that relies on a working independence assumption coupled with a three-step method for obtaining empirical standard errors, and a likelihood-based method implemented using Bayesian computational techniques. Implications of time-varying endogenous covariat...
متن کاملInference on stochastic time-varying coefficient models
Recently there has been considerable work on stochastic time-varying coefficient models as vehicles for modelling structural change in the macroeconomy with a focus on the estimation of the unobserved sample path of time series of coefficient processes. The dominant estimation methods, in this context, are various filters, such as the Kalman filter, that are applicable when the models are cast ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the Korean Data and Information Science Society
سال: 2013
ISSN: 1598-9402
DOI: 10.7465/jkdi.2013.24.3.651