Literature DB >> 28439764

Covariance Model Simulation Using Regular Vines.

Steffen Grønneberg1, Njål Foldnes2.   

Abstract

We propose a new and flexible simulation method for non-normal data with user-specified marginal distributions, covariance matrix and certain bivariate dependencies. The VITA (VIne To Anything) method is based on regular vines and generalizes the NORTA (NORmal To Anything) method. Fundamental theoretical properties of the VITA method are deduced. Two illustrations demonstrate the flexibility and usefulness of VITA in the context of structural equation models. R code for the implementation is provided.

Keywords:  multivariate simulation; non-normality; regular vines; structural equation modeling

Mesh:

Year:  2017        PMID: 28439764     DOI: 10.1007/s11336-017-9569-6

Source DB:  PubMed          Journal:  Psychometrika        ISSN: 0033-3123            Impact factor:   2.500


  6 in total

1.  Generating Nonnormal Multivariate Data Using Copulas: Applications to SEM.

Authors:  Patrick Mair; Albert Satorra; Peter M Bentler
Journal:  Multivariate Behav Res       Date:  2012-07       Impact factor: 5.923

2.  Systems of frequency curves generated by methods of translation.

Authors:  N L JOHNSON
Journal:  Biometrika       Date:  1949-06       Impact factor: 2.445

3.  EVALUATION OF A NEW MEAN SCALED AND MOMENT ADJUSTED TEST STATISTIC FOR SEM.

Authors:  Xiaoxiao Tong; Peter M Bentler
Journal:  Struct Equ Modeling       Date:  2013-01-29       Impact factor: 6.125

4.  How General is the Vale-Maurelli Simulation Approach?

Authors:  Njål Foldnes; Steffen Grønneberg
Journal:  Psychometrika       Date:  2014-08-06       Impact factor: 2.500

5.  A Simple Simulation Technique for Nonnormal Data with Prespecified Skewness, Kurtosis, and Covariance Matrix.

Authors:  Njål Foldnes; Ulf Henning Olsson
Journal:  Multivariate Behav Res       Date:  2016-03-25       Impact factor: 5.923

6.  Asymptotically distribution-free methods for the analysis of covariance structures.

Authors:  M W Browne
Journal:  Br J Math Stat Psychol       Date:  1984-05       Impact factor: 3.380

  6 in total
  2 in total

1.  Partial Identification of Latent Correlations with Binary Data.

Authors:  Steffen Grønneberg; Jonas Moss; Njål Foldnes
Journal:  Psychometrika       Date:  2020-12-21       Impact factor: 2.500

2.  On Identification and Non-normal Simulation in Ordinal Covariance and Item Response Models.

Authors:  Njål Foldnes; Steffen Grønneberg
Journal:  Psychometrika       Date:  2019-09-27       Impact factor: 2.500

  2 in total

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