Generating correlated, non-normally distributed data using a non-linear structural model

DOI10.1007/s11336-015-9468-7zbMath1329.62453OpenAlexW652414656WikidataQ30968781 ScholiaQ30968781MaRDI QIDQ906044

Morten Moshagen, Max Auerswald

Publication date: 29 January 2016

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11336-015-9468-7

zbMATH Keywords

simulationstructural equation modelingnon-normal multivariate data

Mathematics Subject Classification ID

Applications of statistics to psychology (62P15)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A method for simulating non-normal distributions
• How general is the Vale-Maurelli simulation approach?
• A method of simulating multivariate nonnormal distributions by the Pearson distribution system and estimation
• On simulating multivariate non-normal distributions from the generalized lambda distribution
• Simulating multivariate nonnormal distributions
• On simulating non-normal distributions
• Fast fifth-order polynomial transforms for generating univariate and multivariate nonnormal distributions.
• Simulating correlated multivariate nonnormal distributions: extending the Fleishman power method
• Statistical Simulation
• The power method transformation: its probability density function, distribution function, and its further use for fitting data
• An approximate method for generating asymmetric random variables
• SYSTEMS OF FREQUENCY CURVES GENERATED BY METHODS OF TRANSLATION
• Cumulative Frequency Functions

This page was built for publication: Generating correlated, non-normally distributed data using a non-linear structural model