November 🍂: Extensions for time series modeling (measurement models, time varying VAR)
December 🎄: Continuous time models
January ☃️: DSEM/Multilevel time series modeling
February 🧣: Markov Modeling
November 🍂: Extensions for time series modeling (measurement models, time varying VAR)
December 🎄: Continuous time models
January ☃️: DSEM/Multilevel time series modeling
February 🧣: Markov Modeling
Have you considered using latent class DSEM? Or even CT-SEM forests?
Would be very interested to see what heterogeneity can be identified.
Have you considered using latent class DSEM? Or even CT-SEM forests?
Would be very interested to see what heterogeneity can be identified.
これフレシノ喪服着てるよなー
これフレシノ喪服着てるよなー
Sorry if this is way overkill for what started a simple question about means and CIs! 😂
Sorry if this is way overkill for what started a simple question about means and CIs! 😂
lsv1873.de/2026/08/09/l...
lsv1873.de/2026/08/09/l...
#DataScience #Education #Psychology #Statistics #Research #ResearchTraining #Instats
#DataScience #Education #Psychology #Statistics #Research #ResearchTraining #Instats
#Education #Statistics #Psychology #Research #ResearchTraining #Instats
#Education #Statistics #Psychology #Research #ResearchTraining #Instats
Full #openaccess
👉 doi.org/qktp
#PlantScience
Full #openaccess
👉 doi.org/qktp
#PlantScience
🔓 Ketonen, E. E., Kruskopf, M., Lonka, K., & Mattlin, M. (2026). Dynamics of university students’ epistemic emotions during game-based learning in an international relations course. Instructional Science, 54, Article 23. doi.org/10.1007/s112...
🔓 Ketonen, E. E., Kruskopf, M., Lonka, K., & Mattlin, M. (2026). Dynamics of university students’ epistemic emotions during game-based learning in an international relations course. Instructional Science, 54, Article 23. doi.org/10.1007/s112...
And then the follow-up schlock balloons to sure, it ain't an RCT.
And then the follow-up schlock balloons to sure, it ain't an RCT.
A Hybrid NUTS-Gibbs Sampler with State Space Marginalization for Estimation of Dynamic Structural Equation Models with Binomial Outcomes
By S{\o}rensen, McCormick
A Hybrid NUTS-Gibbs Sampler with State Space Marginalization for Estimation of Dynamic Structural Equation Models with Binomial Outcomes
By S{\o}rensen, McCormick
#rstats
https://cran.r-project.org/package=tinyVAST
#rstats
https://cran.r-project.org/package=tinyVAST