easystats
drake
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| easystats | drake | |
|---|---|---|
| 3 | 1 | |
| 1,019 | 1,330 | |
| 2.8% | 0.2% | |
| 7.8 | 6.1 | |
| 7 days ago | about 2 months ago | |
| R | R | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 only |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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.
drake
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Your impression of {targets}? (r package)
The targets package is the official successor to Drake, and has the same primary author (Will Landau). He has explained why he created targets, which includes stronger guardrails for users and better UX.
What are some alternatives?
shinyjs - 💡 Easily improve the user experience of your Shiny apps in seconds
targets - Function-oriented Make-like declarative workflows for R
awesome-R - A curated list of awesome R packages, frameworks and software.
tabulapdf - Bindings for Tabula PDF Table Extractor Library
timevis - 📅 Create interactive timeline visualizations in R
ncaahoopR - An R package for working with NCAA Basketball Play-by-Play Data
fiery - A flexible and lightweight web server
afex - Analysis of Factorial EXperiments (R package)
causalglm - Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning
waffle - :maple_leaf: Make waffle (square pie) charts in R
droll - An R package to analyze roll distributions