Quentin F Gronau

Biographic Data

ID1659965
NAMEQuentin F Gronau
GIVEN NAMESQuentin F
FAMILY NAMEGronau
SIGNATUREGRONAU Q F
AFFILIATIONSUniversity of Amsterdam
ORCID0000-0001-5510-6943
VERIFIEDYes
TOTAL WORKS10
TOTAL CITATIONS25
AUTHOR COUNT10
EDITOR COUNT0
FIRST PUBLICATION YEAR2015
LATEST PUBLICATION YEAR2024
H-INDEX2

  • A unified account of simple and response-selective inhibition

    Open AccessQuentin F Gronau, Mark R Hinder et al.ARTICLECognitive Psychology2024

  • Expert agreement in prior elicitation and its effects on Bayesian inference

    Open AccessAngelika Marlene Stefan, Dimitris Katsimpokis et al.ARTICLEPsychonomic Bulletin & Review2022

    Bayesian inference requires the specification of prior distributions that quantify the pre-data uncertainty about parameter values. One way to specify prior distributions is through prior elicitation, an interview method guiding field experts through the process of expressing their knowledge in the form of a probability distribution. However, prior distributions elicited from experts can be subject to idiosyncrasies of experts and elicitation pro…

  • The Support Interval

    Open AccessEric-Jan Wagenmakers, Quentin F Gronau et al.ARTICLEErkenntnis2022

    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 contains only parameter values that receive at least some minimum amount of support from the data. The…

  • The Jasp guidelines for conducting and reporting a Bayesian analysis

    Open AccessJohnny Van Doorn, Don Van Den Bergh et al.ARTICLEPsychonomic Bulletin & Review2021

    Despite the increasing popularity of Bayesian inference in empirical research, few practical guidelines provide detailed recommendations for how to apply Bayesian procedures and interpret the results. Here we offer specific guidelines for four different stages of Bayesian statistical reasoning in a research setting: planning the analysis, executing the analysis, interpreting the results, and reporting the results. The guidelines for each stage ar…

  • Crowdsourcing hypothesis tests

    Justin F Landy, Miaolei Jia et al.ARTICLEPsychological Bulletin2020Cited by: 9References: 14

    To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer five original research questions related to moral judgments, negotiations, and implicit cognition. Participants from 2 separate large samples (total N > 15,000) were then randomly assigned to complete 1 version of each study. Effect sizes varied dramatically across diff…

  • Jasp

    Open AccessJonathon Love, Ravi Selker et al.ARTICLEJournal of Statistical Software2019

    This paper introduces JASP, a free graphical software package for basic statistical procedures such as t tests, ANOVAs, linear regression models, and analyses of contingency tables. JASP is open-source and differentiates itself from existing open-source solutions in two ways. First, JASP provides several innovations in user interface design; specifically, results are provided immediately as the user makes changes to options, output is attractive,…

  • Bayesian inference for psychology. Part I

    Open AccessEric-Jan Wagenmakers, Marijke Marsman et al.ARTICLEPsychonomic Bulletin & Review2018

    Bayesian parameter estimation and Bayesian hypothesis testing present attractive alternatives to classical inference using confidence intervals and p values. In part I of this series we outline ten prominent advantages of the Bayesian approach. Many of these advantages translate to concrete opportunities for pragmatic researchers. For instance, Bayesian hypothesis testing allows researchers to quantify evidence and monitor its progression as data…

  • Bayesian inference for psychology. Part II

    Open AccessEric-Jan Wagenmakers, Jonathon Love et al.ARTICLEPsychonomic Bulletin & Review2018

    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 were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still repor…

  • The pipeline project

    Open AccessMartin Schweinsberg, Nikhil Madan et al.ARTICLEJournal of Experimental Social…2016Cited by: 16References: 68

    This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replica…

  • Meta-analyses are no substitute for registered replications

    Open AccessMichiel Van Elk, Dora Matzke et al.ARTICLEFrontiers in Psychology2015

    According to a recent meta-analysis, religious priming has a positive effect on prosocial behavior (Shariff et al., 2015). We first argue that this meta-analysis suffers from a number of methodological shortcomings that limit the conclusions that can be drawn about the potential benefits of religious priming. Next we present a re-analysis of the religious priming data using two different meta-analytic techniques. A Precision-Effect Testing-Precis…