Interaction analysis in emmeans

A good first step is always to try to visualize the nature of the interactions before doing any statistical comparisons.

Quick start guide for emmeans

These analyses will yield the estimated marginal means for each factor, and comparisons/contrasts thereof. Back to Contents. Two interacting factors. In this ...

Analysis and visualization of interactions in R (1) - OARC Stats - UCLA

Simple effects analysis with emmeans::contrast() 35. Interaction contrasts ... When using emmeans to analyze the interaction, generally we will need to ...

Pairwise comparisons with emmeans for a mixed three-way ...

Here's what I did: I created a new model with an interaction term (AB = A*B). fit1b <- lmer(rt ~ 1 + A*C + B ...

[Q] interaction analysis with emmeans in R : r/statistics - Reddit

Hi all, I am working on an interaction analysis with 4 regressor. Two of these are factors (F1,F2) while the remaining two are continuous ...

Unleash the Full Power of Models with {emmeans} R-package

Analysing interactions is both (1) very challenging, that's why it's rarely executed, and (2) very rewording if done well, that's why it's ...

Apply custom interaction contrast in emmeans - Stack Overflow

The solution is to split the analysis in three steps: library(afex) library(emmeans) data <- data.frame( id = rep(c(100:189), each = 9), ...

6 Interactions Example | Encyclopedia of Quantitative Methods in R ...

4 Plot Estimated Marginal Means ... The emmeans package can make interaction plots with the emmip() function, but it only can create confidene intervals, not ...

Decomposing, Probing, and Plotting Interactions in R - OARC Stats

This seminar will show you how to decompose, probe, and plot two-way interactions in linear regression using the emmeans package in the R statistical ...

EMMEANS Simple-effect analysis and post-hoc multiple comparison.

Post-hoc multiple comparisons are independent of interaction effects and simple effects. Furthermore, if a simple main effect contains 3 or more levels, we also ...

Basics of estimated marginal means • emmeans - GitHub Pages

The emmeans package requires you to fit a model to your data. All the results obtained in emmeans rely on this model. So, really, the analysis obtained is ...

Getting started with emmeans - Very statisticious

Even if we have multiple factors in the model, complete with an interaction term, we can still do “overall” comparisons among groups if our ...

emmip: Interaction-style plots for estimated marginal means - rdrr.io

If object is a fitted model, emmeans is called with an appropriate specification to obtain estimated marginal means for each combination of the factors present ...

Contrasts and linear functions of EMMs in emmeans - rdrr.io

These methods provide for follow-up analyses of emmGrid objects: Contrasts, pairwise comparisons, tests, and confidence intervals.

Analysis and Visualization of Interactions in R - YouTube

Don't Ignore Interactions - Unleash the Full Power of Models with {emmeans} R-package ... Interaction analysis in R. benR•1.5K views · 13:21.

17.1 emmeans package | A Guide on Data Analysis - Bookdown

Spotlight analysis (Aiken and West 2005): usually pick 3 values of moderating variable: ... The 3 p-values are the same as the interaction term. For publication, ...

Example with interactions

Run the analysis. Run a model with the full interaction between Sex ... To derive the group estimates, you can again use emmeans. The ...

EMMEANS subcommand (ANOVA-F command) - IBM

EMMEANS displays estimated marginal means of the dependent variable in the cells (with covariates held at their overall mean value) and their standard errors.

Change styles of interaction plot using emmeans packages

In my initial comment, I was really trying to suggest that you get the plot data and then start from scratch to produce the plot.

EMMEANS subcommand (ANOVA-M command) - IBM

EMMEANS displays estimated marginal means of the dependent variable in the cells (with covariates held at their overall mean value) and their standard errors.