Correlated ordinal data are common in many areas of research. The data may arise from longitudinal studies in biology, medical, or clinical fields. The prominent characteristic of these data is that the within-subject observations are correlated, whilst between-subject observations are independent. Many methods have been proposed to analyze correlated ordinal data. One way to evaluate the performance of a proposed model or the performance of small or moderate size data sets is through simulation studies. It is thus important to provide a tool for generating correlated ordinal data to be used in simulation studies. In this paper, we describe a macro program on how to generate correlated ordinal data based on R language and SAS IML
In the recent years, a great interest has been devoted by researchers to categorical data and the re...
A modification of the Kaiser and Dichman (1962) procedure of generating multivariate random numbers ...
This dissertation explores different methods to study the dependence structure among many ordinal va...
Statistical tools to analyze correlated binary data are spread out in the existing literature. This ...
In this article, operational details of the R package OrdNor that is designed for the concurrent gen...
57 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008.General computing algorithms a...
This paper provides a brief review of commonly used statistical methods for analyses of ordinal resp...
Studies in epidemiology and social sciences are often longitudinal and outcome measures are frequent...
Ordinal variables appear in many field of statistical research. Since working with simulated data is...
Due to the increasing use of ordinal variables in different fields, new statistical methods for thei...
Studies in epidemiology and social sciences are often longitudinal and outcome measures are frequent...
Studies in epidemiology and social sciences are often longitudinal and outcome measures are frequent...
An alternative approach has been proposed for the analysis and the modelling of ordinal data: it is ...
In this article, we describe a new software for modelling correlated binary data whose raison d’etre...
Ordinal data are used in a lot of domains, especially when measurements are collected from persons b...
In the recent years, a great interest has been devoted by researchers to categorical data and the re...
A modification of the Kaiser and Dichman (1962) procedure of generating multivariate random numbers ...
This dissertation explores different methods to study the dependence structure among many ordinal va...
Statistical tools to analyze correlated binary data are spread out in the existing literature. This ...
In this article, operational details of the R package OrdNor that is designed for the concurrent gen...
57 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008.General computing algorithms a...
This paper provides a brief review of commonly used statistical methods for analyses of ordinal resp...
Studies in epidemiology and social sciences are often longitudinal and outcome measures are frequent...
Ordinal variables appear in many field of statistical research. Since working with simulated data is...
Due to the increasing use of ordinal variables in different fields, new statistical methods for thei...
Studies in epidemiology and social sciences are often longitudinal and outcome measures are frequent...
Studies in epidemiology and social sciences are often longitudinal and outcome measures are frequent...
An alternative approach has been proposed for the analysis and the modelling of ordinal data: it is ...
In this article, we describe a new software for modelling correlated binary data whose raison d’etre...
Ordinal data are used in a lot of domains, especially when measurements are collected from persons b...
In the recent years, a great interest has been devoted by researchers to categorical data and the re...
A modification of the Kaiser and Dichman (1962) procedure of generating multivariate random numbers ...
This dissertation explores different methods to study the dependence structure among many ordinal va...