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
In analyzing longitudinal data the correlations between responses obtained from same individual need...
In this work we propose a new discrete probability distribution useful when we work with ordered cat...
The logistic regression originally is intended to explain the relationship between the probability o...
Azzalini (1994) proposed a first order Markov chain for binary data. Azzalini’s model is extended fo...
The covariate dependence in a higher order Markov models is examined. First order Markov models with...
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...
Repeated or longitudinal ordinal data occur in many fields such as biology, epidemiology, and financ...
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...
Logistic regression models for transition probabilities of higher order Markov models are developed ...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
Repeated or longitudinal ordinal data occur in many fields such as biology, epidemiology, and financ...
SUMMARY. This paper considers the class of sequential ordinal models in relation to other models for...
We consider the analysis of longitudinal ordinal data, meaning regression-like analysis when the res...
In analyzing longitudinal data the correlations between responses obtained from same individual need...
In this work we propose a new discrete probability distribution useful when we work with ordered cat...
The logistic regression originally is intended to explain the relationship between the probability o...
Azzalini (1994) proposed a first order Markov chain for binary data. Azzalini’s model is extended fo...
The covariate dependence in a higher order Markov models is examined. First order Markov models with...
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...
Repeated or longitudinal ordinal data occur in many fields such as biology, epidemiology, and financ...
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...
Logistic regression models for transition probabilities of higher order Markov models are developed ...
Ordinal categorical time series may be analyzed as censored observations from a suitable latent stoc...
Repeated or longitudinal ordinal data occur in many fields such as biology, epidemiology, and financ...
SUMMARY. This paper considers the class of sequential ordinal models in relation to other models for...
We consider the analysis of longitudinal ordinal data, meaning regression-like analysis when the res...
In analyzing longitudinal data the correlations between responses obtained from same individual need...
In this work we propose a new discrete probability distribution useful when we work with ordered cat...
The logistic regression originally is intended to explain the relationship between the probability o...