Latent Markov Models for Longitudinal Data. By F. Bartolucci, A. Farcomeni and F. Nennoni. Boca Raton, Florida: Chapman and Hall/CRC Press 2012. 252 pages. UK £57.99 (hardback). ISBN 978-1-4398-1708-7.

2014 ◽  
Vol 56 (2) ◽  
pp. 196-197
Author(s):  
Geoff Jones
Keyword(s):  
Longitudinal Data ◽  
Markov Models

scholarly journals Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates

Test ◽  
2014 ◽  
Vol 23 (3) ◽  
pp. 433-465 ◽  
Author(s):  
F. Bartolucci ◽  
A. Farcomeni ◽  
F. Pennoni
Keyword(s):  
Longitudinal Data ◽  
General Framework ◽  
Markov Models

Latent Markov Models for longitudinal data

METRON ◽  
2014 ◽  
Vol 72 (3) ◽  
pp. 367-368
Author(s):  
Antonello Maruotti
Keyword(s):  
Longitudinal Data ◽  
Markov Models

Using Longitudinal Data to Model Teachers' Ratings of Classroom Behavior as a Dynamic Process

1981 ◽  
Vol 6 (3) ◽  
pp. 237-255 ◽  
Author(s):  
Ian Plewis
Keyword(s):  
Measurement Error ◽  
Longitudinal Data ◽  
Dynamic Process ◽  
Categorical Data ◽  
Continuous Time ◽  
Classroom Behavior ◽  
Markov Models ◽  
Time Measurement ◽  
Small Sample ◽  
Educational Implications

Simple Markov models are fitted to a small sample of longitudinal categorical data of teachers' ratings of children's classroom behavior. Although the data consist only of observations at 5 occasions, it was possible, after dividing the data into two groups, to fit plausible models in continuous time. Measurement error and alternative longitudinal designs are discussed, and some possible educational implications are noted.

Continuous Time Markov Models for Binary Longitudinal Data

2006 ◽  
Vol 48 (3) ◽  
pp. 411-419 ◽  
Author(s):  
Richard H. Jones ◽  
Stanley Xu ◽  
Gary K. Grunwald
Keyword(s):  
Longitudinal Data ◽  
Continuous Time ◽  
Markov Models ◽  
Binary Longitudinal Data
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