Oisín Ryan

Biographic Data

ID3843818
NAMEOisín Ryan
GIVEN NAMESOisín
FAMILY NAMERyan
SIGNATURERYAN O
AFFILIATIONSUtrecht University
ORCID0000-0003-3698-6396
VERIFIEDYes
TOTAL WORKS10
TOTAL CITATIONS0
WORKS AS AUTHOR10
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2014
LATEST PUBLICATION YEAR2025
H-INDEX0

  • Equilibrium Causal Models

    Open AccessOisín Ryan, Fabian DablanderARTICLEMultivariate Behavioral Research2025

    Many psychological phenomena can be understood as arising from systems of causally connected components that evolve over time within an individual. In current empirical practice, researchers frequently study these systems by fitting statistical models to data collected at a single moment in time, that is, cross-sectional data. This raises a central question: Can cross-sectional data analysis ever yield causal insights into systems that evolve ove…

  • Non-Stationarity in Time-Series Analysis

    Open AccessOisín Ryan, Jonas M B Haslbeck et al.ARTICLEMultivariate Behavioral Research2025

    Time series analysis is increasingly popular across scientific domains. A key concept in time series analysis is stationarity, the stability of statistical properties of a time series. Understanding stationarity is crucial to addressing frequent issues in time series analysis such as the consequences of failing to model non-stationarity, how to determine the mechanisms generating non-stationarity, and consequently how to model those mechanisms (i…

  • Investigating the Relation Between Second Language Proficiency and Study Success Using a Causal Inference Approach

    Open AccessSybren Spit, Sible Andringa et al.ARTICLELanguage Learning2025References: 52

    Prior research suggests that second language (L2) proficiency is key in students' study progress, but this research has mainly been carried out at universities. It is thus unclear how this relation varies across different educational levels. Moreover, previous studies are often not informative about the causality of this relation, making it difficult to base intervention policies on these studies. To address these shortcomings, we analyze a large…

  • Skewness and Staging

    Open AccessMohammadHossein M Haqiqatkhah, Oisín Ryan et al.ARTICLEMultivariate Behavioral Research2024

    low mean, and low variability. In this paper, we investigated whether-and to what extent-the floor effect leads to erroneous conclusions by means of a simulation study. We describe three dynamic models which have meaningful substantive interpretations and can produce floor-effect data. We simulate multilevel data from these models, varying skewness independent of individuals' autoregressive parameters, while also varying the number of time points…

  • Multimodality and skewness in emotion time series

    Open AccessJonas M B Haslbeck, Jonas Haslbeck et al.ARTICLEEmotion2023

    The ability to measure emotional states in daily life using mobile devices has led to a surge of exciting new research on the temporal evolution of emotions. However, much of the potential of these data still remains untapped. In this paper, we reanalyze emotion measurements from seven openly available experience sampling methodology studies with a total of 835 individuals to systematically investigate the modality (unimodal, bimodal, and more th…

  • The Challenge of Generating Causal Hypotheses Using Network Models

    Open AccessOisín Ryan, Laura F Bringmann et al.ARTICLEStructural Equation Modeling: A…2022

    Statistical network models based on Pairwise Markov Random Fields (PMRFs) are popular tools for analyzing multivariate psychological data, in large part due to their perceived role in generating insights into causal relationships: a practice known as causal discovery in the causal modeling literature. However, since network models are not presented as causal discovery tools, the role they play in generating causal insights is poorly understood am…

  • Recovering Within-Person Dynamics from Psychological Time Series

    Open AccessJonas M B Haslbeck, Oisín RyanARTICLEMultivariate Behavioral Research2022

    Idiographic modeling is rapidly gaining popularity, promising to tap into the within-person dynamics underlying psychological phenomena. To gain theoretical understanding of these dynamics, we need to make inferences from time series models about the underlying system. Such inferences are subject to two challenges: first, time series models will arguably always be misspecified, meaning it is unclear how to make inferences to the underlying system…

  • Invisible Hands and Fine Calipers

    Open AccessDonald J Robinaugh, Jonas M B Haslbeck et al.ARTICLEPerspectives on Psychological…2021

    In recent years, a growing chorus of researchers has argued that psychological theory is in a state of crisis: Theories are rarely developed in a way that indicates an accumulation of knowledge. Paul Meehl raised this very concern more than 40 years ago. Yet in the ensuing decades, little has improved. We aim to chart a better path forward for psychological theory by revisiting Meehl’s criticisms, his proposed solution, and the reasons his soluti…

  • A systematic review of Bayesian articles in psychology

    Open AccessRens Van De Schoot, Sonja D Winter et al.ARTICLEPsychological Methods2017

  • Pancultural nostalgia

    Erica G Hepper, Tim Wildschut et al.ARTICLEEmotion2014

    Nostalgia is a frequently experienced complex emotion, understood by laypersons in the United Kingdom and United States of America to (a) refer prototypically to fond, self-relevant, social memories and (b) be more pleasant (e.g., happy, warm) than unpleasant (e.g., sad, regretful). This research examined whether people across cultures conceive of nostalgia in the same way. Students in 18 countries across 5 continents (N = 1,704) rated the protot…