Analysis of correlated data with feedback for time-dependent covariates in psychiatry research

Elsa Vazquez Arreola; Jeffrey R. Wilson; Ding Geng Chen

doi:10.1136/gpsych-2020-100263

Analysis of correlated data with feedback for time-dependent covariates in psychiatry research

Elsa Vazquez Arreola, Jeffrey R. Wilson, Ding Geng Chen

Economics

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

In studies on psychiatry and neurodegenerative diseases, it is common to have data that are correlated due to the hierarchical structure in data collection or to repeated measures on the subject longitudinally. However, the feedback effect created due to time-dependent covariates in these studies is often overlooked and seldom modelled. This article reviews the methodological development of feedback effects with marginal models for longitudinal data and discusses their implementation.

Original language	English (US)
Article number	e100263
Journal	General Psychiatry
Volume	33
Issue number	5
DOIs	https://doi.org/10.1136/gpsych-2020-100263
State	Published - Sep 7 2020

Keywords

biostatistics
longitudinal studies
models, statistical
statistics as topic

ASJC Scopus subject areas

Neurology
Clinical Neurology
Psychiatry and Mental health

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10.1136/gpsych-2020-100263

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N2 - In studies on psychiatry and neurodegenerative diseases, it is common to have data that are correlated due to the hierarchical structure in data collection or to repeated measures on the subject longitudinally. However, the feedback effect created due to time-dependent covariates in these studies is often overlooked and seldom modelled. This article reviews the methodological development of feedback effects with marginal models for longitudinal data and discusses their implementation.

AB - In studies on psychiatry and neurodegenerative diseases, it is common to have data that are correlated due to the hierarchical structure in data collection or to repeated measures on the subject longitudinally. However, the feedback effect created due to time-dependent covariates in these studies is often overlooked and seldom modelled. This article reviews the methodological development of feedback effects with marginal models for longitudinal data and discusses their implementation.

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Analysis of correlated data with feedback for time-dependent covariates in psychiatry research

Abstract

Keywords

ASJC Scopus subject areas

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