Here is a new visualization created in the same manner as my Cohen’s d vizualisation. This new visualization is an interactive display of classical null hypothesis significance testing and statistical power. The visualization should work on mobile phones and tablets, but it requires a modern browser that supports SVG. ... [Read more...]

Earlier this week I read this article about “Why Publishing Everything Is More Effective than Selective Publishing of Statistically Significant Results” by Mercal et al (2014). The authors simulated different meta-analytic scenarios and came to the conclusion that publishing everything is more effective for the scientific collective. This got me thinking ... [Read more...]

I have created a new visualization in D3. The purpose is to aid in the interpretation of Cohen’s d. The visualization presents Cohen’s d in the following ways: Visually, Cohen’s U3, Probability of superiority, Percentage of overlap and Number needed to treat. The visualization should work on ... [Read more...]

I read this post over at the blog Cartesian Faith about Probability and Monte Carlo methods. The post describe how to numerically intregate using Monte Carlo methods. I thought the (…) Read more [Read more...]

A while ago I was playing around with the JavaScript package D3.js, and I began with this visualization—that I never really finished—of how a one-way ANOVA is calculated. I wanted to make the visualization interactive, and I did integrate some interactive elements. For instance, if you hover ... [Read more...]

The practice of classifying treatments as empirically supported (ESTs) has been widely debated for a long time. Recently Jessica Nasser published an article in the Journal of Contemporary Psychotherapy named “Empirically Supported Treatments and Efficacy Trials: What Steps Do We Still Need to Take?”. In the article the author raises ... [Read more...]

A common way of illustrating the idea behind statistical power in null hypothesis significance testing, is by plotting the sampling distributions of the null hypothesis and the alternative hypothesis. Typically, these illustrations highlight the regions that correspond to making a type II error, type I error and correctly rejecting the ... [Read more...]

In this post I show some different examples of how to work with map projections and how to plot the maps using ggplot. Many maps that are using the default projection are shown in the longlat-format, which is far from optimal. Here I show how to use either the Robinson ... [Read more...]

In this post I show some R-examples on how to perform power analyses for mixed-design ANOVAs. The first example is analytical—and adapted from formulas used in G*Power (Faul et al., 2007), and the second example is a Monte Carlo simulation. Read more [Read more...]

The dodo bird might be extinct in the real world but in the world of psychotherapy research it refuses to die. However, a group of German researchers recently put forward an article were they had randomized patients to either a PDT or CBT condition and measured the relative proficiency of ... [Read more...]

Can you tell when error bars based on 95 % CIs or standard errors correspond to a significant p-value? Don’t fret if you think it’s hard, a study from 2005 showed that researchers in psychogoly, behavior neuroscience and medicine had a hard time judging when error bars from two independent groups ... [Read more...]

Why are physicists talking about 5-sigma, and what's it got to do with statistics? In this short post I'll explain what 5-sigma is and why it's not a measure of how certain scientist are that they've found the Higgs boson [Read more...]

When talking about confidence intervals, Jacob Cohen famously said: “I suspect that the main reason they are not reported is that they are so embarrassingly large!” (Cohen, 1994). In this post I'll take a look at the relationship between the 95 % CI for Cohen's d and it's corresponding sample size. [Read more...]

Introduction I've been incredibly busy the last month, amongst other things I've moved about 400 miles from Umeå, in the north of sweden, to Stockholm. However, I've been working a lot with R and especially with power analysis both via Monte Carlo simulations and via analytical approaches. I will not write ... [Read more...]

Which country had the most PubMed citations in 2011? To find out I used R statistical software to analyze the affiliation of 986 427 articles. [Read more...]

Yesterday I wrote an article that looked at the top 20 Cognitive Behavior Therapy journals with the most publications; today I will explain how I did it with R. [Read more...]

In this short article I present some data of the top 20 Cognitive Behavior Therapy (CBT) journals with the most PubMed publications, and compare that to data from 2010 and 2011. [Read more...]

Introduction I recently wrote an article about if mindfulness could aid in insight problem solving. The problem with the study, I referenced to in my article, was that it did not strictly investigate the mechanism behind mindfulness’ effect, or the impact of different techniques. However, last week a new study ... [Read more...]

In this short post I take a look at how to use R and ggplot2 to visualize effect sizes (Cohen’s d) and how to shade the overlapping area of two distributions. [Read more...]

Update: I have created an interactive effect size visualization here Introduction to effect sizes Many times you read in a study that “x and y were significantly different, p __ .05”, which is another way of saying that “assuming that the null hypothesis is true, the probability of getting the observed value ... [Read more...]