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Document type:
Zeitschriftenaufsatz 
Author(s):
Czado, C., Song, P. X.-K. 
Title:
State space mixed models for longitudinal observations with binary and binomial responses 
Abstract:
We propose a new class of state space models for longitudinal discrete response datawhere the observation equation is specified in an additive form involving both deterministic and random linear predictors. These models allow us to explicitly address the effects of trend, seasonal or other time-varying covariates while preserving the power of state space models in modeling serial dependence in the data.We develop aMarkov chainMonte Carlo algorithm to carry out statistical inference for model...    »
 
Keywords:
Longitudinal data, Markov chain Monte Carlo, Probit · Random effects, Regression, Seasonality, Signal-to-noise ratio 
Journal title:
Statistical Papers 
Year:
2008 
Journal volume:
49 
Journal issue:
Pages contribution:
691-714 
Reviewed:
ja 
Language:
en 
Status:
Verlagsversion / published 
Semester:
SS 08 
Format:
Text