patc3

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• This might not be ideal but as a temporary fix in the machine learning module you can uncheck "Scale variables" under "Training Parameters" (both for decision tree and SVM) For the regression module you get the coefficient of det…

  in Predictions with regression tools Comment by patc3 April 20
• Btw I tried some stuff but couldn't figure it out either... am curious to see as well

  in How to release constraints for Measurement Invariance in JASP Comment by patc3 November 2021
• Seems to say you have fewer than 2 people in some group(s) in "prlang"

  in ANOVA data Set Comment by patc3 November 2021
• Edit: Sorry I spoke too fast, I tried with a factor predictor with more than 2 levels and I'm no longer reproducing the fixed effects, seeing as I would need to change the coding as you mention How did you get the chi-square in R? when I do the foll…

  in Reproducing GLMM in R Comment by patc3 October 2021
• Hello, I'm also curious about this (seeing as the results are *very* different). Could I also check out the data or jasp file? My email is patrick.coulombe@d22consulting.com By the way R-hat of 1.145 seems to indicate the chains have not converged (…

  in Discrepant results between non-parametric frequentist and Bayesian independent Samples t-test Comment by patc3 October 2021
• (Adding info here for readers) The source of the discrepancy has been found and fixed: the number of principal components rather than the number of factors was being retrieved by JASP from the parallel analysis. See the corresponding pull request on…

  in Parallel analysis for EFA in JASP Comment by patc3 October 2021
• @jpe @EJ I'm a little late to the show but the source of the discrepancy has been found and fixed: the number of principal components rather than the number of factors was being retrieved by JASP from the parallel analysis. See the corresponding pul…

  in Parallel Analysis in JASP shows persistent discrepancy with R across samples and items Comment by patc3 October 2021