Research Article

MonteCarloSEM: An R Package to Simulate Data for SEM

Volume: 8 Number: 3 September 5, 2021
TR EN

MonteCarloSEM: An R Package to Simulate Data for SEM

Abstract

Monte Carlo simulation is a useful tool for researchers to estimated accuracy of a statistical model. It is usually used for investigating parameter estimation procedure or violation of assumption for some given conditions. To run a simulation either the paid software or open source but free program such as R is need to be used. For that, researchers must have a good knowledge about the theoretical procedures. This paper introduces the R package called MonteCarloSEM. The package helps to simulate and analyze data sets for some simulation condition such as sample size and normality for a given model. Also, an example is given to show how the functions within the package works.

Keywords

References

  1. Boomsma, A. (2013) Reporting Monte Carlo Studies in Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal, 20(3), 518-540. https://doi.org/10.1080/10705511.2013.797839
  2. de Winter, J.C.F. (2013). Using the Student's t-test with extremely small sample sizes. Practical Assessment, Research, and Evaluation, 18, 10. https://doi.org/10.7275/e4r6-dj05
  3. Fleishman, A. I. (1978). A method for simulating non-normal distributions. Psychometrika, 43, 521-532. https://doi.org/10.1007/BF02293811
  4. Higham, N.J. (2009). Cholesky factorization. WIREs Computational Statistics, 1, 251-254.
  5. Maechler, M., & Bates, D. (2006). 2nd Introduction to the Matrix package. URL: https://cran.r-project.org/web/packages/Matrix/vignettes/Intro2Matrix.pdf
  6. Orçan, F. & Yanyun, Y. (2016). A Note on the Use of Item Parceling in Structural Equation Modeling with Missing Data. Journal of Measurement and Evaluation in Education and Psychology, 7 (1), 59-72. https://doi.org/10.21031/epod.88204
  7. Orçan, F. (2020). MonteCarloSEM 0.0.1. https://CRAN.R-project.org/package=MonteCarloSEM
  8. R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Retrieved September 10, 2020, from http://www.R-project.org/

Details

Primary Language

English

Subjects

Studies on Education

Journal Section

Research Article

Publication Date

September 5, 2021

Submission Date

October 2, 2020

Acceptance Date

July 11, 2021

Published in Issue

Year 2021 Volume: 8 Number: 3

APA
Orçan, F. (2021). MonteCarloSEM: An R Package to Simulate Data for SEM. International Journal of Assessment Tools in Education, 8(3), 704-713. https://izlik.org/JA42LF67DE
AMA
1.Orçan F. MonteCarloSEM: An R Package to Simulate Data for SEM. Int. J. Assess. Tools Educ. 2021;8(3):704-713. https://izlik.org/JA42LF67DE
Chicago
Orçan, Fatih. 2021. “MonteCarloSEM: An R Package to Simulate Data for SEM”. International Journal of Assessment Tools in Education 8 (3): 704-13. https://izlik.org/JA42LF67DE.
EndNote
Orçan F (September 1, 2021) MonteCarloSEM: An R Package to Simulate Data for SEM. International Journal of Assessment Tools in Education 8 3 704–713.
IEEE
[1]F. Orçan, “MonteCarloSEM: An R Package to Simulate Data for SEM”, Int. J. Assess. Tools Educ., vol. 8, no. 3, pp. 704–713, Sept. 2021, [Online]. Available: https://izlik.org/JA42LF67DE
ISNAD
Orçan, Fatih. “MonteCarloSEM: An R Package to Simulate Data for SEM”. International Journal of Assessment Tools in Education 8/3 (September 1, 2021): 704-713. https://izlik.org/JA42LF67DE.
JAMA
1.Orçan F. MonteCarloSEM: An R Package to Simulate Data for SEM. Int. J. Assess. Tools Educ. 2021;8:704–713.
MLA
Orçan, Fatih. “MonteCarloSEM: An R Package to Simulate Data for SEM”. International Journal of Assessment Tools in Education, vol. 8, no. 3, Sept. 2021, pp. 704-13, https://izlik.org/JA42LF67DE.
Vancouver
1.Fatih Orçan. MonteCarloSEM: An R Package to Simulate Data for SEM. Int. J. Assess. Tools Educ. [Internet]. 2021 Sep. 1;8(3):704-13. Available from: https://izlik.org/JA42LF67DE

23823             23825             23824