Last updated: 2019-10-31

Checks: 2 0

Knit directory: mcfa-fit/

This reproducible R Markdown analysis was created with workflowr (version 1.4.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.


Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:


Ignored files:
    Ignored:    .RData
    Ignored:    .RDataTmp
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/

Untracked files:
    Untracked:  analysis/fit_boxplots_shiny-app.Rmd
    Untracked:  code/fit-dist-app/

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.


These are the previous versions of the R Markdown and HTML files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view them.

File Version Author Date Message
Rmd 3524c69 noah-padgett 2019-10-31 new shiny app
html 7487ab8 noah-padgett 2019-10-31 Build site.
Rmd 6028223 noah-padgett 2019-10-31 shiny-app demo trial
Rmd 15defd2 noah-padgett 2019-10-19 least-squares estimation method descriptions
html 15defd2 noah-padgett 2019-10-19 least-squares estimation method descriptions

MUCH TO ADD HERE (NOT FINISHED)

The WLSMV fit function has been shown to be:

\[F_{WLSMV}= {\left(s - \sigma(\hat\theta)\right)}^{\prime}W^{-1}{\left(s - \sigma(\hat\theta)\right)}\]

where the interested reader is refered to Muthen (1978) for information on the WLS estimation method more generally, and Muthen (1994) for the general ML-CFA model formulation but to (include references to two-level estimation with WLSMV).

Other Notes

WLSMV takes significantly longer than MLR (i.e., WLSMV was 2-5 minutes per replication compared to MLR which converged in no more than a second or two).

References

  1. Muthén, B. O. (1994). Multilevel Covariance Structure Analysis. Sociological Methods & Research, 22(3), 376–398. https://doi.org/10.1177/0049124194022003006