Last updated: 2020-03-31

Checks: 1 1

Knit directory: mcfa-para-est/

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Ignored files:
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    analysis/figure/
    Ignored:    analysis/site_libs/
    Ignored:    data/compiled_para_results.txt
    Ignored:    data/results_bias_est.csv
    Ignored:    manuscript/
    Ignored:    output/fact-cov-converge-largeN.pdf
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    Ignored:    output/loading-converge-smallN.pdf
    Ignored:    sera-presentation/

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    Modified:   analysis/index.Rmd

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Welcome to our research website on multilevel CFA. On this site, you will find the results of our study on parameter recovery across robust estimation methods for multilevel CFA. We utilizes three different estimators:

  1. MLR: maximum likelihood with robust standard errors
  2. ULSMV: unweighted least squares with mean and variance adjusted \(\chi^2\)
  3. WLSMV: weighted least squares with mean and variance adjusted \(\chi^2\)

This project is additional results from R. Noah Padgett’s master’s thesis project. The simulation project was quite extensive and mainly focused on fit statistics. This project extends that work by using the a subset of the output files to report on parameter recovery.

Admissible Replications

*Admissible Replications and Convergence

Convergence of Estimates Results

*Parameter convergence

Data Cleaning

*Data Cleaning