Web resources, with a particular focus on R and 'tools I actually use'. That is, this doubles as a repository of things I want to have ready access to, as well as a broad guide for people looking for resources for their own statistical explorations. To prevent linkrot, please let me know if any of these hyperlinks are expired.

Data Sets

Indiana University EPA Data Set -- EPA ratings, separated by male/female rater, across many sociological constructs. From Affect Control Theory sociologists. (Relevant to EPA project.)

Graphing

Another nice graphing link for interaction tests -- here.

Katherine Zee - graphing notes -- techniques for making very lovely graphs (see one result in Zee, K. S., Cavallo, J. V., Flores, A. J., Bolger, N., & Higgins, E. T. (2018). Motivation moderates the effects of social support visibility. Journal of personality and social psychology, 114(5), 735-765. ). Note that with careful color selections, you can make the attached look even shinier (as in the Zee et al. article).

R Graph Gallery -- inspiring pieces of "data art" to give ideas for graphing.

Graphing Techniques for Regression, Logistic, MLM -- various ideas and code in R

R and Other Stats Tools

Andrew Hayes -- the website of the guy who gave us PROCESS.

PROCESS -- the website of... PROCESS.

Cruft -- thoughts from my undergraduate supervisor (who happens to be an exceptionally clever guy).

Effect size converter (Hause) -- effect size converter in shinyapps.

estudios -- someone's awesome resource for R functions. It gives an omega-squared estimate for ANOVA in R.

Jason Newsom -- some useful stats gear, including this handy sheet.

Lyons Morris -- convert everything into a Z-score. Handy for crunching a simple meta-analysis.

Nicholas J Rockwood -- extremely useful and clearly-presented MACROS for SPSS, for Item Response Theory and multilevel mediation.

Quant Psy -- tools for mediation and moderation analysis.

Single Paper Meta-analysis -- a very helpful gadget, by McShane & Böckenholt (2017). Meta-analyses statistics within an article to come to more precise estimates.

Stats Tools -- everything about this website is amazing. Has R-code, powerpoint, and sometimes links to videos, about how to do a wide range of stats.

Swirl -- free tools and tutorials for R coding.

Understanding Data -- some helpful techniques for extracting and tabling CFA output from lavaan, and a brief crash course on interpreting and reporting CFA.

Vasser Stats -- pretty much the most useful toolbox for stats I've encountered.

Weighted mean calculator -- simple but essential

R Code

Calculating scales (from https://www.r-bloggers.com/calculating-scale-scores-for-psychological-tests/)

items <- c("attitude3", "attitude6", "attitude8")

scaleKey <- c(1,1,1)

library(psych)

results <- score.items(keys = scaleKey, items = x[items],

totals = FALSE, missing = FALSE, min = 1,

max = 7)

results # Print the results (i.e., reliability and more)

results$score # Extract the actual total score

Function for calculating Mean.X (like the SPSS function): here

MLM

Determining ICC in MLM (NLME) (from Dr. Jill Jacobson's lectures)

#Get ICC through tau and ICC; view ICC

sigmab <- null.model.name$sigma

taub <- diag(sqrt(getVarCov(null.model.name)))

ICC <- (taub^2)/(taub^2 + sigmab^2)

ICC

Correlation Table

Creating a simple correlation table with decent formatting.

(source: https://gist.github.com/abrowman/878f3047d54723b14672)