Regression analysis of sparse asynchronous longitudinal data
نویسندگان
چکیده
منابع مشابه
Regression analysis of sparse asynchronous longitudinal data.
We consider estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent responses and covariates are observed intermittently within subjects. Unlike with synchronous data, where the response and covariates are observed at the same time point, with asynchronous data, the observation times are mismatched. Simple kernel-weighted estimating equations are ...
متن کاملSimultaneous Nonparametric Regression Analysis of Sparse Longitudinal Data
Longitudinal data arise frequently in many scientific inquiries. To capture the dynamic relationship between longitudinal covariates and response, varying coefficient models have been proposed with point-wise inference procedures. This paper considers the challenging problem of asymptotically accurate simultaneous inference of varying coefficient models for sparse and irregularly observed longi...
متن کاملExtension of Logic regression to Longitudinal data: Transition Logic Regression
Logic regression is a generalized regression and classification method that is able to make Boolean combinations as new predictive variables from the original binary variables. Logic regression was introduced for case control or cohort study with independent observations. Although in various studies, correlated observations occur due to different reasons, logic regression have not been studi...
متن کاملA New Nonparametric Regression for Longitudinal Data
In many area of medical research, a relation analysis between one response variable and some explanatory variables is desirable. Regression is the most common tool in this situation. If we have some assumptions for such normality for response variable, we could use it. In this paper we propose a nonparametric regression that does not have normality assumption for response variable and we focus ...
متن کاملFunctional Data Analysis for Sparse Longitudinal Data
We propose a nonparametric method to perform functional principal components analysis for the case of sparse longitudinal data. The method aims at irregularly spaced longitudinal data, where the number of repeated measurements available per subject is small. In contrast, classical functional data analysis requires a large number of regularly spaced measurements per subject. We assume that the r...
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 Royal Statistical Society: Series B (Statistical Methodology)
سال: 2014
ISSN: 1369-7412
DOI: 10.1111/rssb.12086