Logistic regression and other discrete data models for serially correlated observations

DOI10.1007/BF02589225zbMath1446.62233OpenAlexW2042007686MaRDI QIDQ3598303

Adelchi Azzalini

Publication date: 3 February 2009

Published in: Journal of the Italian Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02589225

zbMATH Keywords

Markov chainslongitudinal datarepeated measuresPoisson distributionlogistic regressiondiscrete time seriesmissing databinary datapartial autocorrelation

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items (2)

Likelihood approach for count data in longitudinal experiments ⋮ Bernoulli vector autoregressive model

Cites Work

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• Longitudinal data analysis using generalized linear models
• Discrete analogues of self-decomposability and stability
• Markov Regression Models for Time Series: A Quasi-Likelihood Approach
• Logistic regression for autocorrelated data with application to repeated measures
• A likelihood-based method for analysing longitudinal binary responses
• A Three-Stage Estimator for Studies with Repeated and Possibly Missing Binary Outcomes
• Logistic Regression for Correlated Binary Data

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