| Bayesian statistics and modelling R van de Schoot, S Depaoli, R King, B Kramer, K Märtens, MG Tadesse, ... Nature Reviews Methods Primers 1 (1), 1-26, 2021 | 927 | 2021 |
| The GRoLTS-checklist: guidelines for reporting on latent trajectory studies R Van De Schoot, M Sijbrandij, SD Winter, S Depaoli, JK Vermunt Structural Equation Modeling: A Multidisciplinary Journal 24 (3), 451-467, 2017 | 592 | 2017 |
| Improving transparency and replication in Bayesian statistics: The WAMBS-Checklist. S Depaoli, R Van de Schoot Psychological methods 22 (2), 240, 2017 | 470 | 2017 |
| A systematic review of Bayesian articles in psychology: The last 25 years. R Van De Schoot, SD Winter, O Ryan, M Zondervan-Zwijnenburg, ... Psychological Methods 22 (2), 217, 2017 | 450 | 2017 |
| Bayesian structural equation modeling. D Kaplan, S Depaoli The Guilford Press, 2012 | 315 | 2012 |
| Bayesian analyses: Where to start and what to report R van de Schoot, S Depaoli The European Health Psychologist 16 (2), 75-84, 2014 | 248 | 2014 |
| A Bayesian approach to multilevel structural equation modeling with continuous and dichotomous outcomes S Depaoli, JP Clifton Structural Equation Modeling: A Multidisciplinary Journal 22 (3), 327-351, 2015 | 231 | 2015 |
| Mixture class recovery in GMM under varying degrees of class separation: Frequentist versus Bayesian estimation. S Depaoli Psychological methods 18 (2), 186, 2013 | 171 | 2013 |
| The Importance of Prior Sensitivity Analysis in Bayesian Statistics: Demonstrations Using an Interactive Shiny App S Depaoli, SD Winter, M Visser Frontiers in Psychology 11, 2020 | 127 | 2020 |
| Where do priors come from? Applying guidelines to construct informative priors in small sample research M Zondervan-Zwijnenburg, M Peeters, S Depaoli, R Van de Schoot Research in Human Development 14 (4), 305-320, 2017 | 127 | 2017 |
| Just another Gibbs sampler (JAGS) flexible software for MCMC implementation S Depaoli, JP Clifton, PR Cobb Journal of Educational and Behavioral Statistics 41 (6), 628-649, 2016 | 118 | 2016 |
| The impact of inaccurate “informative” priors for growth parameters in Bayesian growth mixture modeling S Depaoli Structural Equation Modeling: A Multidisciplinary Journal 21 (2), 239-252, 2014 | 102 | 2014 |
| Bayesian statistical methods D Kaplan, S Depaoli Oxford handbook of quantitative methods, 407-437, 2013 | 99 | 2013 |
| Latent growth curve models for biomarkers of the stress response JM Felt, S Depaoli, J Tiemensma Frontiers in neuroscience 11, 315, 2017 | 82 | 2017 |
| Bayesian PTSD-trajectory analysis with informed priors based on a systematic literature search and expert elicitation R van de Schoot, M Sijbrandij, S Depaoli, SD Winter, M Olff, NE Van Loey Multivariate behavioral research 53 (2), 267-291, 2018 | 74 | 2018 |
| Assessment of health surveys: fitting a multidimensional graded response model S Depaoli, J Tiemensma, JM Felt Psychology, health & medicine 23 (sup1), 1299-1317, 2018 | 71 | 2018 |
| An introduction to Bayesian statistics in health psychology S Depaoli, HM Rus, JP Clifton, R van de Schoot, J Tiemensma Health Psychology Review 11 (3), 248-264, 2017 | 57 | 2017 |
| Using person fit statistics to detect outliers in survey research JM Felt, R Castaneda, J Tiemensma, S Depaoli Frontiers in psychology 8, 863, 2017 | 57 | 2017 |
| Iteration of partially specified target matrices: Applications in exploratory and Bayesian confirmatory factor analysis TM Moore, SP Reise, S Depaoli, MG Haviland Multivariate behavioral research 50 (2), 149-161, 2015 | 43 | 2015 |
| Measurement and structural model class separation in mixture CFA: ML/EM versus MCMC S Depaoli Structural Equation Modeling: A Multidisciplinary Journal 19 (2), 178-203, 2012 | 43 | 2012 |
