Personalized treatment for longitudinal data using unspecified random-effects model

Statistica Sinica ◽

10.5705/ss.202015.0120 ◽

2017 ◽

Cited By ~ 2

Author(s):

Hyunkeun Cho ◽

Peng Wang ◽

Annie Qu

Keyword(s):

Longitudinal Data ◽

Random Effects ◽

Personalized Treatment ◽

Random Effects Model

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A Fast Algorithm for Using Semi-Parametric Random Effects Model for Analyzing Longitudinal Data

Statistics Optimization & Information Computing ◽

10.19139/38 ◽

2014 ◽

Vol 2 (4) ◽

Cited By ~ 1

Author(s):

Taban Baghfalaki ◽

Mojtaba Ganjali

Keyword(s):

Longitudinal Data ◽

Random Effects ◽

Fast Algorithm ◽

Random Effects Model

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A correlated random-effects model for normal longitudinal data with nonignorable missingness

Statistics in Medicine ◽

10.1002/sim.3760 ◽

2009 ◽

Vol 29 (2) ◽

pp. 236-247 ◽

Cited By ~ 2

Author(s):

Huazhen Lin ◽

Danping Liu ◽

Xiao-Hua Zhou

Keyword(s):

Longitudinal Data ◽

Random Effects ◽

Random Effects Model ◽

Nonignorable Missingness ◽

Correlated Random Effects

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A Two-Part Random-Effects Model for Semicontinuous Longitudinal Data

Journal of the American Statistical Association ◽

10.1198/016214501753168389 ◽

2001 ◽

Vol 96 (454) ◽

pp. 730-745 ◽

Cited By ~ 307

Author(s):

Maren K Olsen ◽

Joseph L Schafer

Keyword(s):

Longitudinal Data ◽

Random Effects ◽

Random Effects Model

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A Fast Algorithm for Using Semi-Parametric Random Effects Model for Analyzing Longitudinal Data

Statistics Optimization & Information Computing ◽

10.19139/soic.v2i4.38 ◽

2014 ◽

Vol 2 (4) ◽

Author(s):

Taban Baghfalaki ◽

Mojtaba Ganjali

Keyword(s):

Longitudinal Data ◽

Random Effects ◽

Fast Algorithm ◽

Random Effects Model

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Estimation of random-effects model for longitudinal data with nonignorable missingness using Gibbs sampling

Computational Statistics ◽

10.1007/s00180-019-00887-x ◽

2019 ◽

Vol 34 (4) ◽

pp. 1693-1710 ◽

Cited By ~ 1

Author(s):

Prajamitra Bhuyan

Keyword(s):

Longitudinal Data ◽

Gibbs Sampling ◽

Random Effects ◽

Random Effects Model ◽

Nonignorable Missingness

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A Correlated Random Effects Model for Longitudinal Data with Non-ignorable Drop-Out: An Application to University Student Performance

Advanced Statistical Methods for the Analysis of Large Data-Sets ◽

10.1007/978-3-642-21037-2_12 ◽

2011 ◽

pp. 127-136 ◽

Cited By ~ 2

Author(s):

Filippo Belloc ◽

Antonello Maruotti ◽

Lea Petrella

Keyword(s):

Longitudinal Data ◽

Student Performance ◽

Random Effects ◽

University Student ◽

Drop Out ◽

Random Effects Model ◽

Correlated Random Effects

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Longitudinal data analysis using Bayesian-frequentist hybrid random effects model

Journal of Applied Statistics ◽

10.1080/02664763.2014.898137 ◽

2014 ◽

Vol 41 (9) ◽

pp. 2001-2010

Author(s):

Le Chen ◽

Ao Yuan ◽

Aiyi Liu ◽

Guanjie Chen

Keyword(s):

Data Analysis ◽

Longitudinal Data ◽

Random Effects ◽

Longitudinal Data Analysis ◽

Random Effects Model

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199. The Random Effects Model Applied to RCF Workplace Monitoring Data

10.3320/1.2763037 ◽

1999 ◽

Author(s):

L. Maxim ◽

J. Allshouse ◽

D. Venturin

Keyword(s):

Random Effects ◽

Monitoring Data ◽

Random Effects Model ◽

Workplace Monitoring

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Measurement Invariance Testing Using Random Effects model for Many groups: Multilevel Confirmatory Factor Analysis (ML CFA) and Multilevel Factor Mixture Modeling (ML FMM)

THE KOREAN JOURNAL OF PSYCHOLOGY GENERAL ◽

10.22257/kjp.2019.6.38.2.185 ◽

2019 ◽

Vol 38 (2) ◽

pp. 185-218

Author(s):

Sookyung Son ◽

Hyojin Kim ◽

Sehee Hong

Keyword(s):

Factor Analysis ◽

Confirmatory Factor Analysis ◽

Measurement Invariance ◽

Random Effects ◽

Mixture Modeling ◽

Random Effects Model ◽

Invariance Testing ◽

Multilevel Confirmatory Factor Analysis ◽

Factor Mixture Modeling ◽

Confirmatory Factor

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Variable selection for semiparametric random-effects conditional density models with longitudinal data

Communication in Statistics- Theory and Methods ◽

10.1080/03610926.2018.1554130 ◽

2018 ◽

Vol 49 (4) ◽

pp. 977-996

Author(s):

Xiaohui Yuan ◽

Yue Wang ◽

Tianqing Liu

Keyword(s):

Variable Selection ◽

Longitudinal Data ◽

Random Effects ◽

Conditional Density ◽

Selection For

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