Bad news: did you know that you can get desirable psychometric properties (high correlations, high reliability, good model fit) with *totally* meaningless survey items?

Good news: if you use the Response Process Evaluation method, you could prevent that from happening.

osf.io/preprints/ps...

Thanks so much for looking into this so quickly!! It's still installing OpenMx :(

I think it may be because of this function: github.com/SachaEpskamp....

I'm so frustrated about this OpenMx error 😭 fingers crossed for a resolution soon. I really liked semPlot.

I'm trying to display a preview in a shiny app for users (just as a check that the model statement they entered generally looks okay). Outside of R, I'm a big fan of draw.io!

I'll try this one, thanks!!

Is there a good alternative to #semplot for path diagrams in #R? I'm getting error messages trying to install dependencies (specifically, #openmx) on my linux server 😭

Thanks for the reminder! Excellent work.

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Also, when is BS getting the poll feature?!

When creating a psychological instrument, have you ever tested the interpretability of your survey items within the target population?

New print w/@MelissaGWolf on dynamic fit index cutoffs.

Our software can now derive customized DFI cutoffs for ANY covariance structure model (CFA, SEM, mediation, bifactor, etc.) and supports normal, non-normal, categorical, and missing data (and any estimator) 1/9

psyarxiv.com/4r9fq

Thanks so much! That makes sense.

When writing up results from a study that was pre-registered, do you reference your hypotheses from the pre-registration?

FYI, if you want to post a RMD file as a reprex on #StackOverflow or elsewhere, just put ~~~ at the beginning and end of the code. For example:
~~~
---
title: "My RMD"
---

Some text.

```{r}
library(tidyverse)
```
```{r}
head(mydat)
```
~~~