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Software: Learn R
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Software: Learn R
Resources to learn and use the Open Source Statistical software R (R-Project)
Start Here
R You Lost?
Tutorials
Exploration & Teaching
Data Management
Statistical Analysis
Graphics
Data Science
Good Practices
If you do not know R yet, check out
jamovi
, a point-and-click statistical software that uses R.
Packages by Analysis
afex
– ANOVA (also mixed models with lme4)
emmeans
– Postestimation tests
lme4
– Mixed Models
lavaan
– Structural Equation Modeling
survival
– Survival Models
survey
OR
srvyr - Complex Samples
More Useful Packages
Multi-Purpose
psych
- Many functions for Psychology
TidyModels
- Modeling compatible with the Tidyverse
easystats
- collection of packages for working with models
insight
- extract information from model objects
report
- produces APA-style model results in text
see
- produces relevant ggplot graphics from a model object
Publication-Specific
gtsummary
- create publication-ready analytical and summary tables
pander, kable, and stargazer are older alternatives
equatiomatic
- create the equation for a fitted model in LaTeX
Learning Statistics with R
Tutorials
YouTube Channel
Simplistics (Quant Psych)
- Eccentric teacher is good at simplifying complex topics.
Fast-paced with background music.
This large collection covers everything from the basics to mixed models, both theoretically and in R.
YouTube Channel
StatQuest with Josh Starmer "in R"
- Various topics in R step-by-step
Statistics and machine learning
(yuzaR Data Science)
Multivariable Linear Regression in R
(~20 minutes)
YouTube Channel
Global Health
&
YouTube Channel
R Programing 101
- Greg Martin, Medicine / Public Health
Has additional
free
(registration required) and
paid
resources
MarinStatsLectures
&
YouTube Channel
- Mike Marin
, Statistics / Public Health
Videos created for graduate students at The University of British Columbia
Formula Notation Reference
Formulas
(Social Science Computing Cooperative) - Examples of using formulas for plots and analyses up to regression.
Model Specification
(GLMM FAQ by Ben Bolker/lme4) - Specifying random effects / mixed models in lme4 and nlme
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