Multivariate analysis is commonly used when we have more than one outcome variables for each observation. For instance, a survey of American adults’ physical and mental health might measure each ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 43, No. 3 (September/septembre 2015), pp. 337-357 (21 pages) Multivariate ordinal data are modelled as a finite ...

Multivariate meta-regression models are commonly used in settings where the response variable is naturally multidimensional. Such settings are common in cardiovascular and diabetes studies where the ...

Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variables under consideration. Multivariate analysis techniques may be used for several ...

Linear regression-based quantitative trait loci/association mapping methods such as least squares commonly assume normality of residuals. In genetics studies of plants or animals, some quantitative ...

This paper develops a simple model for measuring potential output that uses data on inflation, unemployment, and capacity utilization. We apply the model to 10 countries, in addition to the United ...