#statstab #523 Equal vs. Proportional Weighting in Least-Squares Means

Thoughts: Interesting comparisons of bias for the two methods. Complex stuff.

I wonder what people make of this.

#weighting #error #bias #LSM #emmeans #covariates

https://imazubi.github.io/stats/stats_equal_vs_proportional_lsm/index_equal_vs_proportional_lsm.html

#statstab #341 ANOVA and Post-Hoc Contrasts

Thoughts: A nice step-by-step tutorial on using different anova functions in R and emmeans for contrasts.

#anova #emmeans #r #guide #tutorial

https://cran.r-project.org/web/packages/afex/vignettes/afex_anova_example.html

#statstab #323 Counterfactuals and G-Computation

Thoughts: Even {emmeans} can do funky stuff for observational studies, if that is your fancy.

#gcomputation #counterfactuals #observational #R #emmeans #design

https://cran.r-project.org/web/packages/emmeans/vignettes/messy-data.html#counterfact

#statstab #317 Tests for Pairwise Mean Differences in R
by @timmastny

Thoughts: A nice illustration of what {emmeans} is doing when computing contrasts using various functions.

#emmeans #r #pairwise #ttest #tutorial #dataviz

https://timmastny.com/blog/tests-pairwise-categorical-mean-emmeans-contrast/

Really like the Notes on emmeans::eff_size(). It basically says "this might not be doing what you think. there are lots of decision you need to make. it's easy to get unexpected results. it's all your fault if you do" 😕

(also it's the emm version of d, not raw data d; i wonder what underscore symbol to use)
#emmeans

#statstab #213 Marginal means and Average predictions

Thoughts: Do you prefer Estimated Marginal Means or Average Predictions? Care to report an Average Counterfactual Adjusted Prediction or an AME? Here are some options:

#r #emmeans #marginaleffects

https://marginaleffects.com/bonus/alternative_software.html

#statstab #162 Post-hoc Contrasts by {rcompanion}

Thoughts: A good tutorial should always be shared. This goes step-by-step and provides options. Including plots.

#stats #emmeans #posthoc #ttest #nhst #r #dataviz #models

https://rcompanion.org/rcompanion/h_01.html

#statstab #17 {emmeans} for unpacking interactions

Thoughts: Neither SPSS, JASP, or Jamovi can give you all the stats to unpack/report a 3x3 mixed ANOVA. But it's super easy with emmeans. Also learned "joint = TRUE" for simple effects.

#stats #rstats #statstodon #emmeans #anova

https://cran.r-project.org/web/packages/emmeans/vignettes/interactions.html

The minimum effect is my power threshold so they cancel each other out. How can I do this? Preferably with linear models in r (I like `emmeans` and `simr`.

@lakens you wrote that more power is needed for minimum effects compared to null tests, so you might know.

I have asked here but gotten no response https://stats.stackexchange.com/questions/621178/power-analysis-for-minimum-effect-tests-and-good-enough-range-hypotheses

#statistics #rstats #emmeans #data #datascience