منابع مشابه
Conditional Dependence in Longitudinal Data Analysis
Mixed models are widely used to analyze longitudinal data. In their conventional formulation as linear mixed models (LMMs) and generalized LMMs (GLMMs), a commonly indispensable assumption in settings involving longitudinal non-Gaussian data is that the longitudinal observations from subjects are conditionally independent, given subject-specific random effects. Although conventional Gaussian...
متن کاملLongitudinal Discriminant Analysis with Random Effects for Predicting Preeclampsia using Hematocrit Data
Background and Objectives: Preeclampsia is the third leading cause of death in pregnant women. This study was conducted to evaluate the ability of longitudinal hematocrit data to predict preeclampsia and to compare the accuracy in longitudinal and cross-sectional data. Materials and Methods: In a prospective cohort study from October 2010 to July 2011, 650 pregnant women referred to the prenata...
متن کاملLongitudinal Data Analysis Using Generalized Linear Models
This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence. The estimating equations are derived without specifying the joint distribution of a subject's observations yet they redu...
متن کاملOrdinal longitudinal data analysis
Growth data and longitudinal data in general are often of an ordinal nature. For example, developmental stages may be classified into ordinal categories and behavioral variables repeatedly measured by discrete ordinal scales. Consider the data set presented in Table 15.1. This table contains information on marijuana use taken from five annual waves (1976–80) of the National Youth Survey (Elliot...
متن کاملLongitudinal Functional Data Analysis.
We consider dependent functional data that are correlated because of a longitudinal-based design: each subject is observed at repeated times and at each time a functional observation (curve) is recorded. We propose a novel parsimonious modeling framework for repeatedly observed functional observations that allows to extract low dimensional features. The proposed methodology accounts for the lon...
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: Zeitschrift Fur Erziehungswissenschaft
سال: 2023
ISSN: ['1862-5215', '1434-663X']
DOI: https://doi.org/10.1007/s11618-023-01155-x