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This page collects links to tutorials and other online resources we have found useful for SCS clients.

Graphical methods

• Royal Statistical Society . Insights, advice, and examples (with code) to make data outputs more readable, accessible, and impactful.

• . This post by Rob Hyndman, describes some best practices for producing graphs for journal publication.

• . The guide proposes a simple reproducible project workflow, and a guide to organizing projects for reproducibility. The Programming section provides concrete tips and traps to avoid (example: use relative, not absolute pathnames), and the Reproducible Reports section provides a step-by-step guide for generating reports with R Markdown.

Multiplicity Control

Negligible Effect (Equivalence) Testing

. Equivalency testing, a statistical method often used in biostatistics to determine the equivalence of 2 experimental drugs, is introduced to social scientists. Examples of equivalency testing are offered, and the usefulness of the method to the social scientist is discussed.

Lakens et al.

• describes the TOSTER package.
• The provides functions that are useful for conducting negligible effect testing (also called equivalence testing),
  including equivalence of means or the presence of a negligible association (correlation or regression)

Linear models (ANOVA, Regression)

• . An overview of R packages and functions for fitting different types of linear models, classified by the type
  of outcome variable (continuous, binary, catgegorical). Contains links to examples and shows Bayesian equivalents of many frequentist approaches.
• . modelsummary is an R a package to summarize data and statistical models in R. It supports over one hundred types of models out-of-the-box, and allows users to report the results of those models side-by-side in a table, or in coefficient plots. There is also a that condenses many examples into a shorter format.

Meta Analysis

• Mathais Harrer . An accessible introduction into how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools.

Structural Equation Models

• 
  pwrSEM is a Shiny web app that researchers can use to conduct power analysis for structural equation models. Tutorial papers for pwrSEM can be found at: ;

Effect size & power analysis

• Matthew B Jane et al. . This guide aims to provide academics, students and researchers with hands-on, step-by-step instructions for calculating effect sizes and confidence intervals for common statistical tests used in the behavioral, cognitive and social sciences.
• Metin Bulus . An online application with power / sample size calculators for a wide variety of statistical problems.

Latent Profile Analysis

Latent profile analysis (LPA) is a latent variable method that focuses on identifying latent sub-populations within a population based on observed variables.
LPA works best with continuous variables (and, in some cases, ordinal variables), but is not appropriate for dichotomous (binary) variables.

• Spurk et al.
• . The tidyLPA package provides an interface to the powerful and widely-used mclust package for Gaussian Mixture Modeling.