easystats
afex
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easystats | afex | |
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1,019 | 114 | |
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7.8 | 5.8 | |
7 days ago | 18 days ago | |
R | R | |
GNU General Public License v3.0 or later | - |
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easystats
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My recommended R packages / functions for behavioral researchers who deal with 2X2 experiments
I'd also recommend the whole easystats suite of packages. They make model post-processing much easier. It includes a more intuitive (but more limited, imo) replacement for emmeans: modelbased.
- Most useful new packages (or package updates) from the last 3 years
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ISO a holy grail RStudio tutorial account, specifically for data analysis in psychology.
The Easystats suite, which includes several packages. It's extremely useful for Bayesian analyses, but even if you stay on the frequentist side, I recommend its performance, parameters, effectsize and correlation packages. Performance is particularly useful in conjunction to DHARMa for model diagnostic and comparison.
afex
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My recommended R packages / functions for behavioral researchers who deal with 2X2 experiments
afex is great for ANOVAs. It gives you type 3 SS by default too, and includes methods for bootstrapping. It was specifically made for experimental/factorial designs iirc. It also handles mixed effect regressions by calling lme4. You can even specify repeated measures ANOVA with the same syntax as mixed effect models.
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Setting up Mixed Effects ANOVA
The package afex does both ANOVA and LMM, and gives you an ANOVA-like table of main effects for both.
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How can I do what I do in SPSS via R? (Pictures added)
SPSS defaults to type III sum of squares for ANOVAs [1], but aov() does not. Different results suggest that you probably have unbalanced data. But it's difficult to know what model you ran because you did not provide valid R code. In general, I'd recommend that you use the afex package for ANOVA in R.
What are some alternatives?
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waffle - :maple_leaf: Make waffle (square pie) charts in R
Practical-Applications-in-R-for-Psychologists - Lesson files for Practical Applications in R for Psychologists.
ggstatsplot - Enhancing {ggplot2} plots with statistical analysis 📊📣
MicrobiomeStat - Track, Analyze, Visualize: Unravel Your Microbiome's Temporal Pattern with MicrobiomeStat
HoRM - Supplemental Functions and Datasets for "Handbook of Regression Methods"
rcanvas - R Client for Canvas LMS API