Stat’s What It’s All About

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Working with Ordinal Ranks in `{marginaleffects}`

R

statistics

code

marginaleffects

Given an ordinal regression model, it is relatively easy to get class-wise predictions - the conditional predicted probability of each level of the outcome. However, often…

Centering in Moderation Analysis: A Guide

R

statistics

code

datawaizard

moderation

interactions

This blog post will cover what centering is, what a sum-to-zero contrast is, why and when you should use them, and how you can do them in R. Specifically, we will focus on…

Order Constraints in Bayes Models (with `brms`)

R

statistics

code

Bayes

Stan

Over a year ago, while listing to a very not-at-all-statistical podcast, I discovered that Bayesian modeling is widely used in archaeology since the mid 90s to calibrate…

Ordinal Regression as a Model for Signal Detection

R

statistics

code

ordinal regression

signal detection theory

I was basically done with this blog post when I came across Matti Vuorre’s post on the same exact topic. Matti goes into all the details, and really the present post can be…

ggplot: Easy as pie (charts)

R

ggplot2

_{This post by no means endorses the use of pie charts. But, if you must, here’s how…}

ggplot: plot only some of the data

R

ggplot2

Often (especially when working with large and/or rich datasets) our (gg)plots can feel cluttered with information. But they don’t have to be!

Everything You Always Wanted to Know About ANOVA*

(*But Were Afraid to Ask)

statistics

R

regression

ANOVA

interactions

linear models

code

glm

Analysis of variance (ANOVA) is a statistical procedure, developed by R. A. Fisher, used to analyze the relationship between a continuous outcome (dependent variable) and…

ggplot: the placing and order of aesthetics matters

R

ggplot2

A group of people were asked to what degree they agree or disagree with a statement at two time points.

Testing The Equality of Regression Coefficients

statistics

R

regression

emmeans

You have two predictors in your model. One seems to have a stronger coefficient than the other. But is it significant?

(What to do) When Predictors Co-Vary

statistics

R

emmeans

code

glm

multicollinearity

assumptions

Co-varying predictors can be a messy business. They make estimates unstable, reducing our statistical power and making interpretation more difficult. In this post I will…