## About

41

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Introduction

## Publications

Publications (41)

We introduce the statistical concept known as likelihood and discuss how
it underlies common Frequentist and Bayesian statistical methods. This
article is suitable for researchers interested in understanding the basis of
their statistical tools, and is also ideal for teachers to use in their classrooms
to introduce the topic to students at a concep...

We introduce the fundamental tenets of Bayesian inference, which derive from two basic laws of probability theory. We cover the interpretation of probabilities, discrete and continuous versions of Bayes' rule, parameter estimation , and model comparison.

This article brings attention to some historical developments that gave rise to the Bayes factor for testing a point null hypothesis against a composite alternative. In line with current thinking, we find that the conceptual innovation - to assign prior mass to a general law - is due to a series of three articles by Dorothy Wrinch and Sir Harold Je...

We revisit the results of the recent Reproducibility Project: Psychology by the Open Science Collaboration. We compute Bayes factors-a quantity that can be used to express comparative evidence for an hypothesis but also for the null hypothesis-for a large subset (N = 72) of the original papers and their corresponding replication attempts. In our co...

Testing the equality of two proportions is a common procedure in science, especially in medicine and public health. In these domains, it is crucial to be able to quantify evidence for the absence of a treatment effect. Bayesian hypothesis testing by means of the Bayes factor provides one avenue to do so, requiring the specification of prior distrib...

Testing the equality of two proportions is a common procedure in science, especially in medicine and public health. In these domains it is crucial to be able to quantify evidence for the absence of a treatment effect. Bayesian hypothesis testing by means of the Bayes factor provides one avenue to do so, requiring the specification of prior distribu...

A frequentist confidence interval can be constructed by inverting a hypothesis test, such that the interval contains only parameter values that would not have been rejected by the test. We show how a similar definition can be employed to construct a Bayesian support interval. Consistent with Carnap’s theory of corroboration, the support interval co...

The target article on robust modeling (Lee et al. in review) generated a lot of commentary. In this reply, we discuss some of the common themes in the commentaries; some are simple points of agreement while others are extensions of a practical or abstract nature. We also address a small number of disagreements or confusions.

The open science movement is rapidly changing the scientific landscape. Because exact definitions are often lacking and reforms are constantly evolving, accessible guides to open science are needed. This paper provides an introduction to open science and related reforms in the form of an annotated reading list of seven peer-reviewed articles, follo...

The target article on robust modeling (Lee et al.) generated a lot of commentary. In this reply, we discuss some of the common themes in the commentaries; some are simple points of agreement while others are extensions of a practical or abstract nature. We also address a small number of disagreements or confusions.

In an attempt to increase the reliability of empirical findings, psychological scientists have recently proposed a number of changes in the practice of experimental psychology. Most current reform efforts have focused on the analysis of data and the reporting of findings for empirical studies. However, a large contingent of psychologists build mode...

In an attempt to increase the reliability of empirical findings, psychological scientists have recently proposed a number of changes in the practice of experimental psychology. Most current reform efforts have focused on the analysis of data and the reporting of findings for empirical studies. However, a large contingent of psychologists build mode...

A frequentist confidence interval can be constructed by inverting a hypothesis test, such that the interval contains only parameter values that would not have been rejected by the test. We show how a similar definition can be employed to construct a Bayesian support interval. Consistent with Carnap’s theory of corroboration, the support interval co...

Self-control is assessed using a remarkable array of measures. In a series of five data-sets (overall N = 2,641) and a mini meta-analysis, we explored the association between canonical operationalisations of self-control: The Self-Control Scale and two measures of inhibition-related executive functioning (the Stroop and Flanker paradigms). Overall,...

Few scientific developments are as divisive as the increasingly popular Open Science movement. Because exact definitions are lacking and reforms are constantly evolving, accessible guides to Open Science are needed. This paper provides an introduction to Open Science and related reforms in the form of an annotated reading list of 8 peer-reviewed ar...

This report outlines: a) a need for objective, transparent and usable criteria for judging the decision-readiness of published research evidence and b) the many, important research challenges associated with producing such criteria and ensuring their uptake in the scientific community and beyond. It was produced by Focus Group 2 at TECSS.

I provide some technical notes regarding the Kullback-Leibler divergence. Derivations of the Kullback-Leibler divergence are provided for Bernoulli, Geometric, Poisson, Exponential, and Normal distributions.

We describe a general method that allows experimenters to quantify the evidence from the data of a direct replication attempt given data already acquired from an original study. These so-called replication Bayes factors are a reconceptualization of the ones introduced by Verhagen and Wagenmakers (Journal of Experimental Psychology: General, 143(4),...

Across the social sciences, researchers have overwhelmingly used the classical statistical paradigm to draw conclusions from data, often focusing heavily on a single number: p. Recent years, however, have witnessed a surge of interest in an alternative statistical paradigm: Bayesian inference, in which probabilities are attached to parameters and m...

The commentaries on our target article are insightful and constructive. There were some critical notes, but many commentaries agreed with, or even amplified our message. The first section of our response addresses comments pertaining to specific parts of the target article. The second section provides a response to the commentaries' suggestions to...

Hypothesis testing is a special form of model selection. Once a pair of competing models is fully defined, their definition immediately leads to a measure of how strongly each model supports the data. The ratio of their support is often called the likelihood ratio or the Bayes factor. Critical in the model-selection endeavor is the specification of...

The commentaries on our target article are insightful and constructive. There were some critical notes, but many commentaries agreed with, or even amplified our message. The first section of our response addresses comments pertaining to specific parts of the target article. The second section provides a response to the commentaries' suggestions to...

Hypothesis testing is a special form of model selection. Once a pair of competing models is fully defined, their definition immediately leads to a measure of how strongly each model supports the data. The ratio of their support is often called the likelihood ratio or the Bayes factor. Critical in the model selection endeavor is the specification of...

Psychology journals rarely publish nonsignificant results. At the same time, it is often very unlikely (or “too good to be true”) that a set of studies yields exclusively significant results. Here, we use likelihood ratios to explain when sets of studies that contain a mix of significant and nonsignificant results are likely to be true or “too true...

Many philosophers of science and methodologists have argued that the ability to repeat studies and obtain similar results is an essential component of science. A finding is elevated from single observation to scientific evidence when the procedures that were used to obtain it can be reproduced and the finding itself can be replicated. Recent replic...

Many philosophers of science and methodologists have argued that the ability to repeat studies and obtain similar results is an essential component of science. A finding is elevated from single observation to scientific evidence when the procedures that were used to obtain it can be reproduced and the finding itself can be replicated. Recent replic...

We introduce the statistical concept known as likelihood and discuss how it underlies common Frequentist and Bayesian statistical methods. This article is suitable for researchers interested in understanding the basis of their statistical tools, and is also ideal for teachers to use in their classrooms to introduce the topic to students at a concep...

Self-control is assessed using a remarkable array of measures. However, the ability to override impulses putatively unites diverse measures of self-control. In a series of four studies (N = 2,463) and a mini meta-analysis, we explored the association between two canonical operationalisations of self-control: The Self-Control Scale and inhibition-re...

We describe a general method that allows experimenters to quantify the evidence from the data of a direct replication attempt given data already acquired from an original study. These so-called replication Bayes factors are a reconceptualization of the ones introduced by Verhagen and Wagenmakers (2014) for the common t-test. This reconceptualizatio...

Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data wer...

In this guide, we present a reading list to serve as a concise introduction to Bayesian data analysis. The introduction is geared toward reviewers, editors, and interested researchers who are new to Bayesian statistics. We provide commentary for eight recommended sources, which together cover the theoretical and practical cornerstones of Bayesian s...

Across the social sciences, researchers have overwhelmingly used the classical statistical paradigm to draw conclusions from data, often focusing heavily on a single number: p. Recent years, however, have witnessed a surge of interest in an alternative statistical paradigm: Bayesian inference, in which probabilities are attached to parameters and m...

We introduce the fundamental tenets of Bayesian inference, which derive from two basic laws of probability theory. We cover the interpretation of probabilities, discrete and continuous versions of Bayes' rule, parameter estimation, and model comparison. Using seven worked examples, we illustrate these principles and set up some of the technical bac...

Psychology journals rarely publish non-significant results. At the same time, it is often very unlikely (or ‘too good to be true’) that a set of studies yields exclusively significant results. Here, we use likelihood ratios to explain when sets of studies that contain a mix of significant and non-significant results are likely to be true, or ‘too t...

In this guide, we present a reading list to serve as a concise introduction to Bayesian data analysis. The introduction is geared toward reviewers, editors, and interested researchers who are new to Bayesian statistics. We provide commentary for eight recommended sources, which together cover the theoretical and practical cornerstones of Bayesian s...

In their 2015 paper, Thorstenson, Pazda, and Elliot offered evidence from two experiments that perception of colors on the blue–yellow axis was impaired if the participants had watched a sad movie clip, compared to participants who watched clips designed to induce a happy or neutral mood. Subsequently, these authors retracted their article, citing...

In their article reporting the results of two experiments, Thorstenson, Pazda, & Elliot (2015a) found evidence that perception of colors on the blue-yellow axis was impaired if the participants had watched a sad movie clip, relative to participants who watched clips designed to induce a happy or neutral mood. Subsequently, these authors retracted t...

Table.
Inferential statistics for each of the 72 studies and their replicates.
(PDF)

Children are exceptional, even 'super,' imitators but comparatively poor independent problem-solvers or innovators. Yet, imitation and innovation are both necessary components of cumulative cultural evolution. Here, we explored the relationship between imitation and innovation by assessing children's ability to generate a solution to a novel proble...

Recent studies suggest that target-to-object relationship (whether the target appears to be a part of the object or is perceived as placed on top of an object) is the primary factor that determines whether attentional guidance is influenced by object representations (Chen & Cave, 2006; Richard, Lee, & Vecera, 2008; Hollingworth, Maxcey-Richard, and...

## Projects

Projects (2)

Illustrate and discuss methodological practices in cognitive modeling that can lead to advances in model-based inferences.

In this guide, we present a reading list to serve as a concise introduction to Bayesian data analysis. The introduction is geared toward reviewers, editors, and interested researchers who are new to Bayesian statistics. We provide commentary for eight recommended sources, which together cover the theoretical and practical cornerstones of Bayesian statistics in psychology and related sciences.