#statstab #345 Best practices for your confirmatory factor analysis: A JASP and lavaan tutorial

Thoughts: Don't want to install #R but still want to do SEM/CFA with {lavaan}, @JASPStats is your friend!

#CFA #FactorAnalysis #SEM #tutorial #EFA #JASP

https://rdcu.be/eme1V

#statstab #344 Questionable Research Practices when Using Confirmatory Factor Analysis

Thoughts: CFAs might be better than EFAs, but they are still complicated and easy to abuse.

#factoranalysis #CFA #QRPs #fitindex #guide

https://dr.lib.iastate.edu/bitstreams/4efe4918-7cad-4db1-b3cc-44825cbb6e08/download

An adversarial collaboration reports that mathematical reflection tests assess #math ability about as much as anything else. 😬

And what is the evidence that the paper's “independent” measure of reflection actually measured reflection? 🧐

https://doi.org/10.1073/pnas.2409191121

#psychometrics #psychology #cogPsych #JDM #decisionScience #economics #factorAnalysis #stats #rStats

TL;DR: It's not a psychometric scale and it's not weebly

This "Weebly racism scale" has been posted a couple of times on the Fediverse, and I finally decided to look it up. It seems like a multidimensional construct reduced to one dimension, so I wanted to see the items, hopefully an exploratory #FactorAnalysis, evidence of #reliability and (dare I hope?) #validity.

Yeah, no. It's not a scale at all, in the psychometric sense. No data collection or #analysis (AFAICT) was part of this, so there is no (and, at this point, can be no) validity information.

This is one person's ideas about racism. This is absolutely the kind of thought work that should be done when one is at the very beginning of scale creation, but it's not a scale like that.

The scale is hosted on weebly dot com, a web host kind of like squarespace.

The fact that hundreds (or thousands) of other people resonate with this scale is a good sign for potential validity. However, that is not sufficient psychometric evidence to call this a "racism scale" alongside things like the Modern Racism Scale, etc.

This seems like a useful activity to get you thinking about your experiences with racism (on either side of that line), but because it's not a psychometric scale, there's no *scientific* reason to believe

* The implied or explicit categories map onto actual racist thinking/behavior patterns

* The order of the categories is valid--e.g., there's no evidence "I'm not racist but..." is more racist than "'Funny' Black Face", etc.

* The categories even belong on the same continuum

As I said above, it really feels like a decent start, but with several dimensions squashed into one. I'd personally love to see a racism researcher use this to develop an actual scale, or try to. I suspect the result would be something vaguely resembling this scale but with significant differences.

#psychometrics #psychology #racism #prejudice #scale #discrimination #scaleconstruction

*

#statstab #129 Structural Models (EFA, CFA, SEM, ...) w/ {parameters}

Thoughts: Lots of debate about #EFA vs #CFA; very confusing. Once I figure out what to use, this #R package seems to have lots of functionality.

#rstats #factoranalysis #r #stats

https://easystats.github.io/parameters/articles/efa_cfa.html

Our new article on evaluating (qualitative changes in) emotional granularity/differentiation in
#ESM
data led by Marcel Schmitt has now been published in MBR :-) https://www.tandfonline.com/doi/full/10.1080/00273171.2024.2328381 #measurement #psychometrics #factoranalysis #affect

PCA focuses on maximizing variance and transforming variables into principal components, while Factor Analysis seeks to model the underlying structure and relationships among variables through latent factors.

PCA in R programming online course starting on April 02: https://statisticsglobe.com/online-course-pca-theory-application-r

#DataScience #Statistics #PCA #FactorAnalysis #RStats

"The Kaiser-Meyer-Olkin value was 0.94, which means that the sample size is adequate for #FactorAnalysis."

#PeerReview #NightshiftEditor #Psychometrics

These four #Python #tutorials introduce and discuss #PCA, #tsne, #factoranalysis, and #Autoencoder as powerful tools for #DimensionalityReduction:

🌍 https://www.fabriziomusacchio.com/blog/2023-06-16-pca_with_python/
🌍 https://www.fabriziomusacchio.com/blog/2023-06-12-tsne_vs_pca/
🌍 https://www.fabriziomusacchio.com/blog/2023-06-16-factoranalysis_with_python/
🌍 https://www.fabriziomusacchio.com/blog/2023-06-16-autoencoder_with_python/

Feel free to share, use and remix 😊🙏

#tutorial

Quote from the popular Tucker & Lewis paper on a reliability coefficient for maximum likelihood #FactorAnalysis.

#Psychometrics #History