Sebastian Castro-Alvarez
@SeCastroAl
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Postdoctoral researcher at the University of Groningen, The Netherlands. Not using X lately. Find me on LinkedIn.
Groningen, The Netherlands
Joined March 2021
Thank you for checking it out! 🙏
This paper on intensive longitudinal reliability by @SeCastroAl & @bringmann_laura is one of the best I've read in a while -- the review so was thorough, the code was fantastic, and it answered every question I had about IL reliability. Def check it out! https://t.co/mxrgdxKlco
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La Fundación Carolina ha abierto la convocatoria de una beca para estudiantes de América Latina que quieran cursar el Master en Metodología en 2025/26. + info: https://t.co/iZDosXTQm9 Gracias a @Red_Carolina
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¡Qué felicidad! Cerramos el año de la mejor manera: @Casa_Macondo entró al shortlist de los True Story Awards con la investigación #ElArchivoSecreto. Gracias, @HaciaElUmbral, por tu generosidad, disciplina y rigor en este proyecto. ¡Un logro compartido!
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Go check out our latest preprint! Thank you @EikoFried and colleagues for sharing the data. It has been very interesting and insightful data to work with!
1/2 Our new preprint shows how to estimate internal consistency reliability in EMA data: ➡️n~1150, 3 months data, 4 scales ➡️6 nomothetic & idiographic methods ➡️2 timescales (4/day, 1/week) ➡️2 languages (ENG vs NL) ➡️separation of between & within person reliability.
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Now online: 📏Assessing and Accounting for Measurement in Intensive Longitudinal Studies: Current Practices, Considerations, and Avenues for Improvement https://t.co/V5i4nmtzQC (with @JoranJongerling and Esther Maassen) #measurement #psychometrics #ESM
link.springer.com
Quality of Life Research - Intensive longitudinal studies, in which participants complete questionnaires multiple times a day over an extended period, are increasingly popular in the social...
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The final version of the paper is also now out! 🥳
journals.sagepub.com
The daily social life of a person can be captured with different methodologies. Two methods that are especially promising are personal-social-network (PSN) data...
📢 New preprint! 📢 Interested in capturing the social life of participants? We describe how ESM can be combined with personal social networks (PSN). This combination delivers detailed data on social interactions and social relationships. 💬👥 https://t.co/OWFpMs6lU3
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Excited to share our latest preprint in collaboration with @bringmann_laura, Jason Back, and Siwei Liu. In this manuscript, we explain different approaches to estimate the reliability of ESM data while showing how to use them with empirical data.
The Many Reliabilities of Psychological Dynamics: An Overview of Statistical Approaches to Estimate the Internal Consistency Reliability of Intensive Longitudinal Data
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No-data psychometric testing with a click! NLP and AI will boost psychometric testing research quality and speed. Based on recent research, I have built a beta version of a shinyapp for conducting psychometric testing on text data only. #Psychometrics #CostSavings #aiapplications
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Code to fit the model in @mcmc_stan and custom R functions to assess its goodness of fit are available in the GitHub repository associated with both papers:
github.com
Dynamic Item Response Theory. Contribute to secastroal/DIRT development by creating an account on GitHub.
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Thanks to this contribution, empirical researchers interested in analyzing their data with the TV-DPCM will also be able to assess how well the model fits their data.
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In a nutshell, when using the PPMC method, one compares given test statistics as computed based on the observed data to the distribution of the given test statistics as computed based on simulated data. Large differences imply a lack of fit.
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The test statistics were developed within the posterior predictive model checking method (PPMC). This is a Bayesian procedure commonly used to assess the goodness of fit of Bayesian models.
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In this paper, we proposed several test statistics to assess the goodness of fit of the time-varying partial credit model (TV-DPCM). This is an IRT model to analyze multivariate time series data. For more details on the model, see our previous publication:
tandfonline.com
The accessibility to electronic devices and the novel statistical methodologies available have allowed researchers to comprehend psychological processes at the individual level. However, there are ...
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The last paper of my PhD: "Assessment of fit of the time-varying dynamic partial credit model using the posterior predictive model checking method", is finally out! https://t.co/6XtpMQB2DM In collaboration with Sandip Sinharay, @bringmann_laura, Rob Meijer, and Jorge Tendeiro
bpspsychub.onlinelibrary.wiley.com
Several new models based on item response theory have recently been suggested to analyse intensive longitudinal data. One of these new models is the time-varying dynamic partial credit model (TV-DP...
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You know you’ve made when you see your first print byline is a front page article @queenseagle. S/o to @jacob_kaye_ for the opportunity! Click link below to read the full story about the hurdles of disabled migrants in New York City. https://t.co/8dtxqQy1D8
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A mis contactos en Bogotá, invitados a la obra Kabus producida por mi hermana Natalia Castro y su compañía DanceBog Ballet
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Are you doing research with ESM & wondering how to make your data ready for analysis? Check the new preprint introducing a comprehensive framework for preprocessing ESM data developed by @JordanRevol. https://t.co/oZMNakASfq materials include a tutorial website and R functions
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In the empirical example, we also show how to compute and interpret the item characteristic functions and the information functions. These are core features in IRT modeling that provide further insights into the quality of the scale.
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