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Herbert Hoijtink

Herbert Hoijtink

D-Index & Metrics

Social Sciences and Humanities

D-Index
42
Citations
8919
World Ranking
4679
National Ranking
188

Overview

Herbert Hoijtink is affiliated with Utrecht University in the Netherlands. Their research primarily focuses on advanced statistical methods and Bayesian inference, with specific attention to statistical methods in clinical trials and animal testing.

Their published works span various domains within mathematics and psychology, emphasizing statistical methods and models. The main fields of study include:

  • Mathematics

Subfields cover a diverse range:

  • Statistics and Probability
  • Clinical Psychology
  • Small Animals
  • Experimental and Cognitive Psychology
  • Computer Networks and Communications

Hoijtink has contributed to several focused topics:

  • Statistical Methods and Bayesian Inference
  • Statistical Methods in Clinical Trials
  • Advanced Statistical Methods and Models
  • Advanced Statistical Modeling Techniques
  • Animal testing and alternatives
  • Metabolomics and Mass Spectrometry Studies
  • Sensory Analysis and Statistical Methods

Their recent papers include:

  • A review of applications of the Bayes factor in psychological research., 2022, Psychological Methods
  • Increasing the statistical power of animal experiments with historical control data, 2021, Nature Neuroscience
  • BFpack: Flexible Bayes Factor Testing of Scientific Theories in R, 2021, Journal of Statistical Software
  • Sample-size determination for the Bayesian t test and Welch's test using the approximate adjusted fractional Bayes factor, 2020, Behavior Research Methods
  • Robust longitudinal multi-cohort results: The development of self-control during adolescence, 2020, Developmental Cognitive Neuroscience

Frequent co-authors collaborating with Hoijtink are:

  • Caspar J. Van Lissa
  • Joris Mulder
  • Mariëlle Zondervan-Zwijnenburg
  • Zoltán Dienes
  • Qianrao Fu

Common publication venues for their work include:

  • Psychological Methods
  • Developmental Cognitive Neuroscience
  • Meta-Psychology
  • Nature Neuroscience
  • Behavior Research Methods

Best Publications

  • Redefine statistical significance

    Daniel J. Benjamin;James O. Berger;Magnus Johannesson;Magnus Johannesson;Brian A. Nosek;Brian A. Nosek

  • Bayesian estimation and testing of structural equation models

    Richard Scheines;Herbert Hoijtink;Anne Boomsma

  • Inequality Constrained Analysis of Variance: A Bayesian Approach.

    Irene Klugkist;Olav Laudy;Herbert Hoijtink

  • Reliability and validity of the Dutch version of the inventory of traumatic grief (ITG).

    Paul A Boelen;Jan Van Den Bout;Jos De Keijser;Herbert Hoijtink

  • The many null distributions of person fit indices

    Ivo W. Molenaar;Herbert Hoijtink

  • A tutorial on testing hypotheses using the Bayes factor.

    Herbert Hoijtink;Joris Mulder;Caspar van Lissa;Xin Gu

  • The Multidimensionality of Self-Report Schizotypy in a Psychiatric Population: An Analysis Using Multidimensional Rasch Models

    Meinte G. Vollema;Herbert Hoijtink

  • The Best of Both Worlds: Factor Analysis of Dichotomous Data Using Item Response Theory and Structural Equation Modeling

    Angelika Glockner-Rist;Herbert Hoijtink

  • Informative Hypotheses: Theory and Practice for Behavioral and Social Scientists

    Herbert Hoijtink

  • The Bayes factor for inequality and about equality constrained models

    Irene Klugkist;Herbert Hoijtink

  • Bayesian Evaluation of Informative Hypotheses

    Herbert Hoijtink;Irene Klugkist;Paul A Boelen

  • A multidimensional item response model: Constrained latent class analysis using the gibbs sampler and posterior predictive checks

    Herbert Hoijtink;Ivo W. Molenaar

  • Equality and inequality constrained multivariate linear models: objective model selection using constrained posterior priors

    Joris Mulder;Herbert Hoijtink;Irene Klugkist

  • The role of executive functions in numerical magnitude skills

    Meijke E. Kolkman;Herbert J.A. Hoijtink;Evelyn H. Kroesbergen;Paul P.M. Leseman

  • BIEMS : A Fortran 90 program for calculating Bayes factors for inequality and equality constrained models

    C. de Leeuw;H. Hoijtink;J. Mulder

  • Bayesian model selection using encompassing priors

    Irene Klugkist;Bernet Kato;Herbert Hoijtink

  • Bayesian model selection of informative hypotheses for repeated measurements

    Joris Mulder;Irene Klugkist;Rens van de Schoot;Wim H.J. Meeus

  • A latent trait model for dichotomous choice data

    Herbert Hoijtink

  • On person parameter estimation in the dichotomous Rasch model

    Herbert Hoijtink;Anne Boomsma

  • Intraindividual variability in infant behavior.

    C. de Weerth;P. L. C. Van Geert;H.J.A. Hoijtink

  • Approximated adjusted fractional Bayes factors: A general method for testing informative hypotheses

    Xin Gu;Xin Gu;Joris Mulder;Herbert Hoijtink

Frequent Co-Authors

Rens van de Schoot
Rens van de Schoot Utrecht University
Paul A. Boelen
Paul A. Boelen Utrecht University
Wim Meeus
Wim Meeus Utrecht University
Thomas D. Cook
Thomas D. Cook University of Wisconsin–Madison
Eric-Jan Wagenmakers
Eric-Jan Wagenmakers University of Amsterdam
David Cesarini
David Cesarini New York University
Yves Rosseel
Yves Rosseel Ghent University
Brian A. Nosek
Brian A. Nosek Center for Open Science
Zoltan Dienes
Zoltan Dienes University of Sussex
Dorret I. Boomsma
Dorret I. Boomsma Vrije Universiteit Amsterdam

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