Row and column matrices in multiple correspondence analysis with ordered categorical and dichotomous variables
In multiple correspondence analysis, whenever the number of variables exceeds the number of observations, row matrix should be used, but if the number of variables is less than the number of observations column matrix is the suitable procedure to follow. One of the following matrices (rows, columns)...
Main Authors: | Thanoon, Thanoon Y., Adnan, Robiah |
---|---|
Format: | Article |
Language: | English |
Published: |
Penerbit UTM Press
2016
|
Subjects: | |
Online Access: | http://eprints.utm.my/73885/1/RobiahAdnan2016_RowAndColumnMatricesInMultiple.pdf |
Similar Items
-
Bayesian analysis of multiple group nonlinear structural equation models with ordered categorical and dichotomous variables:a survey
by: Thanoon, Y. Thanoon, et al.
Published: (2015) -
Bayesian approach to structural equation models for ordered categorical and dichotomous data
by: Thanoon, Y. Thanoon
Published: (2017) -
Model comparison of Bayesian structural equation models with mixed ordered categorical and dichotomous data
by: Thanoon, T. Y., et al.
Published: (2017) -
Bayesian analysis of multiple group nonlinear structural equation models with ordered categorical data
by: Thanoon, Thanoon Y., et al.
Published: (2015) -
Comparison between Bayesian structural equation models with ordered categorical data
by: Thanoon, T. Y., et al.
Published: (2016)