Ladislas Nalborczyk - Blogposts

Making sense of commonality analysis

Statistics

RSA

Cognitive neuroscience

Using commonality analysis to identify unique and shared (common) variance across three or more variables.

Ladislas Nalborczyk

The Meehlian Corroboration-Verisimilitude Theory of Science - Part II

Philosophy of science

Paul Meehl

The second part of my compiled reading notes on Meehl’s metatheory and related meta-peregrinations.

Ladislas Nalborczyk

The Meehlian Corroboration-Verisimilitude Theory of Science - Part I

Philosophy of science

Paul Meehl

My compiled reading notes on Meehl’s metatheory and related meta-peregrinations.

Ladislas Nalborczyk

What does a Bayes factor look like?

R

Data visualisation

Bayes factor

Bayesian

An attempt to illustrate what a Bayes factor looks like, using GIFs.

Ladislas Nalborczyk

Checking the asumption of independence in binomial trials using posterior predictive checking

Tutorial

R

Bayesian

PPC

As put by Gelman et al. (2013, page 148): ‘because a probability model can fail to reflect the process that generated the data in any number of ways, posterior predictive p-values can be computed for a variety of test quantities in order to evaluate more than one possible model failure’.

Ladislas Nalborczyk

Using R to make sense of the generalised linear model

Tutorial

R

GLM

What is the difference between the errors and the residuals? What does it mean for a model to predict something? What is a link function? In the current post, we use four R functions (the predict, fitted, residuals and simulate functions) to illustrate the mechanisms and assumptions of the generalised linear model.

Ladislas Nalborczyk

Three methods for computing the intra-class correlation in multilevel logistic regression

R

Bayesian

brms

Intra-class correlation

Multilevel regression

In the current post, we present and compare three methods of obtaning an estimation of the ICC in multilevel logistic regression models.

Ladislas Nalborczyk

The saga of the summer 2017, a.k.a. ‘the alpha wars’

NHST

alpha wars

A short summary of the “alpha wars” that occurred during the summer of year 2017.

Ladislas Nalborczyk

Experimental absenteeism and logistic regression - Part II

R

Bayesian

brms

Logistic regression

Multilevel model

This post continues our exploration of the logistic regression model by extending it to a multilevel logistic regression model, using the brms package.

Ladislas Nalborczyk

Experimental absenteeism and logistic regression - Part I

R

Bayesian

Logistic regression

This post aims to assess the average probability of participant presence in psychological experiments and, in the meantime, to introduce Bayesian logistic regression using R and the rethinking package.

Ladislas Nalborczyk

Why the Akaike information criterion is as much ‘Bayesian’ as the Bayesian information criterion

Bayesian

Model comparison

According to Rubin (1984), a Bayesianly justifiable analysis is one that “treats known values as observed values of random variables, treats unknown values as unobserved random variables, and calculates the conditional distribution of unknowns given knowns and model specifications using Bayes’ theorem”.

Ladislas Nalborczyk