# Posts

### How to analyze visual analog (slider) scale data?

A reasonable choice might be the zero-one-inflated beta model

### Combine ggplots with patchwork

How to combine arbitrary ggplots

### Bayesian Estimation of Signal Detection Models

Signal Detection Theory (SDT) is a popular theoretical framework for modeling memory and perception. Calculating point estimates of equal variance Gaussian SDT parameters is easy using widely known formulas. More complex SDT models, such as the unequal variance SDT model, require more complicated modeling techniques. These models can be estimated using Bayesian (nonlinear and/or hierarchical) regression methods, which are illustrated here.

### How to create within-subject scatter plots in R with ggplot2

Scatterplots can be a very effective form of visualization for data from within-subjects experiments. You’ll often see within-subject data visualized as bar graphs (condition means, and maybe mean difference if you’re lucky.) But alternatives exist, and today we’ll take a look at within-subjects scatterplots.

### How to Compare Two Groups with Robust Bayesian Estimation in R

2017 will be the year when social scientists finally decided to diversify their applied statistics toolbox, and stop relying 100% on null hypothesis significance testing (NHST). A very appealing alternative to NHST is Bayesian statistics, which in itself contains many approaches to statistical inference. In this post, I provide an introductory and practical tutorial to Bayesian parameter estimation in the context of comparing two independent groups’ data.

### How to arrange ggplot2 panel plots

Arrange your visual display of information to maximize your figures’ impact.

### Bayesian Meta-Analysis with R, Stan, and brms

Meta-analysis is a special case of Bayesian multilevel modeling

### GitHub-style waffle plots in R

Attractive visualization for plotting activity over time in R with ggplot2.

### How to create plots with subplots in R

Some tips on creating figures with multiple panels in R