Topics
Markov chainElection
Azzalini (1994) proposed a first order Markov chain for binary data. Azzalini’s model is extended for ordinal data and introduces a second order model. Further, the test statistics are developed and the power of the test is determined. An application using real data is also presented. Key words: Markov chain, serial correlation, longitudinal data, ordinal data, covariate dependence, repeated measures
We consider longitudinal studies with binary outcomes that are measured repeatedly on subjects over ...
The analysis of longitudinal data where the response variable is binary is considered from the point...
The paper proposes a full information maximum likelihood estimation method for modelling multivariat...
Azzalini (1994) proposed a first order Markov chain for binary data. Azzalini’s model is extended fo...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
We consider the analysis of longitudinal ordinal data, meaning regression-like analysis when the res...
SUMMARY. This paper considers the class of sequential ordinal models in relation to other models for...
The covariate dependence in a higher order Markov models is examined. First order Markov models with...
We consider longitudinal studies with binary outcomes that are measured repeatedly on subjects over ...
In this dissertation we consider a first-order Markov dependence model for a short sequence of corre...
In this paper we study higher-order Markov chain models for analyzing categorical data sequences. We...
We consider longitudinal studies with binary outcomes that are measured repeatedly on subjects over ...
The analysis of longitudinal data where the response variable is binary is considered from the point...
The paper proposes a full information maximum likelihood estimation method for modelling multivariat...
Azzalini (1994) proposed a first order Markov chain for binary data. Azzalini’s model is extended fo...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
We consider the analysis of longitudinal ordinal data, meaning regression-like analysis when the res...
SUMMARY. This paper considers the class of sequential ordinal models in relation to other models for...
The covariate dependence in a higher order Markov models is examined. First order Markov models with...
We consider longitudinal studies with binary outcomes that are measured repeatedly on subjects over ...
In this dissertation we consider a first-order Markov dependence model for a short sequence of corre...
In this paper we study higher-order Markov chain models for analyzing categorical data sequences. We...
We consider longitudinal studies with binary outcomes that are measured repeatedly on subjects over ...
The analysis of longitudinal data where the response variable is binary is considered from the point...
The paper proposes a full information maximum likelihood estimation method for modelling multivariat...
Add to ORKG