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Titel:

State space mixed models for longitudinal observations with binary and binomial responses

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Czado, C., Song, P. X.-K.
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 models...     »
Stichworte:
Longitudinal data, Markov chain Monte Carlo, Probit · Random effects, Regression, Seasonality, Signal-to-noise ratio
Zeitschriftentitel:
Statistical Papers
Jahr:
2008
Band / Volume:
49
Heft / Issue:
4
Seitenangaben Beitrag:
691-714
Reviewed:
ja
Sprache:
en
WWW:
http://link.springer.com/article/10.1007%2Fs00362-006-0039-y
Status:
Verlagsversion / published
Semester:
SS 08
Format:
Text
 BibTeX