Maarten Marsman
@maartenmarsman.bsky.social
Assistant Professor at the University of Amsterdam
Pinned
🚀 bgms 0.1.6.0 is now on CRAN!
New in this release:
• NUTS & HMC sampling for bgm() + bgmCompare()
• Parallel chains + reproducible runs via seed
• Markov chain diagnostics (ESS, R-hat)
• New summary(), print(), and coef() methods
🔗https://cran.r-project.org/web/packages/bgms/index.html
New in this release:
• NUTS & HMC sampling for bgm() + bgmCompare()
• Parallel chains + reproducible runs via seed
• Markov chain diagnostics (ESS, R-hat)
• New summary(), print(), and coef() methods
🔗https://cran.r-project.org/web/packages/bgms/index.html
🚀 Our paper on Bayes factor tests for the differences in networks (graphical models) in two independent groups is now online at Psychometrika: doi.org/10.1017/psy....
Of course, these methods are implemented in the bgms R package, which now also allows testing more than two independent groups.
Of course, these methods are implemented in the bgms R package, which now also allows testing more than two independent groups.
Bayes Factor Tests for Group Differences in Ordinal and Binary Graphical Models | Psychometrika | Cambridge Core
Bayes Factor Tests for Group Differences in Ordinal and Binary Graphical Models
doi.org
November 4, 2025 at 1:10 PM
🚀 Our paper on Bayes factor tests for the differences in networks (graphical models) in two independent groups is now online at Psychometrika: doi.org/10.1017/psy....
Of course, these methods are implemented in the bgms R package, which now also allows testing more than two independent groups.
Of course, these methods are implemented in the bgms R package, which now also allows testing more than two independent groups.
Reposted by Maarten Marsman
Bamojax (Bayesian modelling with JAX) v0.3.10 is out! Next to increased support for distributions and bijectors, several marginal likelihood estimators are now available, such as bridge sampling and truncated harmonic mean estimation (THAMES).
Check it out on github.com/UncertaintyI...!
Check it out on github.com/UncertaintyI...!
GitHub - UncertaintyInComplexSystems/bamojax: Bayesian Modelling using Jax
Bayesian Modelling using Jax. Contribute to UncertaintyInComplexSystems/bamojax development by creating an account on GitHub.
github.com
October 15, 2025 at 2:14 PM
Bamojax (Bayesian modelling with JAX) v0.3.10 is out! Next to increased support for distributions and bijectors, several marginal likelihood estimators are now available, such as bridge sampling and truncated harmonic mean estimation (THAMES).
Check it out on github.com/UncertaintyI...!
Check it out on github.com/UncertaintyI...!
🚀 bgms 0.1.6.0 is now on CRAN!
New in this release:
• NUTS & HMC sampling for bgm() + bgmCompare()
• Parallel chains + reproducible runs via seed
• Markov chain diagnostics (ESS, R-hat)
• New summary(), print(), and coef() methods
🔗https://cran.r-project.org/web/packages/bgms/index.html
New in this release:
• NUTS & HMC sampling for bgm() + bgmCompare()
• Parallel chains + reproducible runs via seed
• Markov chain diagnostics (ESS, R-hat)
• New summary(), print(), and coef() methods
🔗https://cran.r-project.org/web/packages/bgms/index.html
September 27, 2025 at 9:06 PM
🚀 bgms 0.1.6.0 is now on CRAN!
New in this release:
• NUTS & HMC sampling for bgm() + bgmCompare()
• Parallel chains + reproducible runs via seed
• Markov chain diagnostics (ESS, R-hat)
• New summary(), print(), and coef() methods
🔗https://cran.r-project.org/web/packages/bgms/index.html
New in this release:
• NUTS & HMC sampling for bgm() + bgmCompare()
• Parallel chains + reproducible runs via seed
• Markov chain diagnostics (ESS, R-hat)
• New summary(), print(), and coef() methods
🔗https://cran.r-project.org/web/packages/bgms/index.html
Reposted by Maarten Marsman
Exciting #rstats news for Bayesian model comparison: bridgesampling is finally ready to support cmdstanr, see screenshot. Help us by installing the development version of bridgesampling and letting us know if it works for your model(s): pak::pkg_install("quentingronau/bridgesampling#44")
![R code and output showing the new functionality:
``` r
## pak::pkg_install("quentingronau/bridgesampling#44")
## see: https://cran.r-project.org/web/packages/bridgesampling/vignettes/bridgesampling_example_stan.html
library(bridgesampling)
### generate data ###
set.seed(12345)
mu <- 0
tau2 <- 0.5
sigma2 <- 1
n <- 20
theta <- rnorm(n, mu, sqrt(tau2))
y <- rnorm(n, theta, sqrt(sigma2))
### set prior parameters ###
mu0 <- 0
tau20 <- 1
alpha <- 1
beta <- 1
stancodeH0 <- 'data {
int<lower=1> n; // number of observations
vector[n] y; // observations
real<lower=0> alpha;
real<lower=0> beta;
real<lower=0> sigma2;
}
parameters {
real<lower=0> tau2; // group-level variance
vector[n] theta; // participant effects
}
model {
target += inv_gamma_lpdf(tau2 | alpha, beta);
target += normal_lpdf(theta | 0, sqrt(tau2));
target += normal_lpdf(y | theta, sqrt(sigma2));
}
'
tf <- withr::local_tempfile(fileext = ".stan")
writeLines(stancodeH0, tf)
mod <- cmdstanr::cmdstan_model(tf, quiet = TRUE, force_recompile = TRUE)
fitH0 <- mod$sample(
data = list(y = y, n = n,
alpha = alpha,
beta = beta,
sigma2 = sigma2),
seed = 202,
chains = 4,
parallel_chains = 4,
iter_warmup = 1000,
iter_sampling = 50000,
refresh = 0
)
#> Running MCMC with 4 parallel chains...
#>
#> Chain 3 finished in 0.8 seconds.
#> Chain 2 finished in 0.8 seconds.
#> Chain 4 finished in 0.8 seconds.
#> Chain 1 finished in 1.1 seconds.
#>
#> All 4 chains finished successfully.
#> Mean chain execution time: 0.9 seconds.
#> Total execution time: 1.2 seconds.
H0.bridge <- bridge_sampler(fitH0, silent = TRUE)
print(H0.bridge)
#> Bridge sampling estimate of the log marginal likelihood: -37.73301
#> Estimate obtained in 8 iteration(s) via method "normal".
#### Expected output:
## Bridge sampling estimate of the log marginal likelihood: -37.53183
## Estimate obtained in 5 iteration(s) via method "normal".
```](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:lgxrkw556dtxkplwrj5rzlli/bafkreicf6zdyyjmaxrdfyq2sekokprym3c2o5atca6i2cczcx5zec4q4hm@jpeg)
September 2, 2025 at 9:16 AM
Exciting #rstats news for Bayesian model comparison: bridgesampling is finally ready to support cmdstanr, see screenshot. Help us by installing the development version of bridgesampling and letting us know if it works for your model(s): pak::pkg_install("quentingronau/bridgesampling#44")
Reposted by Maarten Marsman
De redactie verzweeg het feit dat de voorstellen van GL-Pvda volledig onderschreven wordt door het WRR-rapport Goede Zaken. Geen manipulatietechniek wordt geschuwd om de oppositie kapot te maken.
July 20, 2025 at 2:13 AM
De redactie verzweeg het feit dat de voorstellen van GL-Pvda volledig onderschreven wordt door het WRR-rapport Goede Zaken. Geen manipulatietechniek wordt geschuwd om de oppositie kapot te maken.
Reposted by Maarten Marsman
Fair coins tend to land on the same side they started: evidence from 350,757 flips.
That's the title of our paper summarizing ~650 hours of coin-tossing experimentation just published in the Journal of the American Statistical Association.
doi.org/10.1080/0162...
That's the title of our paper summarizing ~650 hours of coin-tossing experimentation just published in the Journal of the American Statistical Association.
doi.org/10.1080/0162...
August 11, 2025 at 2:20 PM
Fair coins tend to land on the same side they started: evidence from 350,757 flips.
That's the title of our paper summarizing ~650 hours of coin-tossing experimentation just published in the Journal of the American Statistical Association.
doi.org/10.1080/0162...
That's the title of our paper summarizing ~650 hours of coin-tossing experimentation just published in the Journal of the American Statistical Association.
doi.org/10.1080/0162...
Reposted by Maarten Marsman
New paper with @richarddmorey.bsky.social now out in JASA, where we critically examine p-curve. Below is Richard’s excellent summary of the many poor statistical properties of p-curve (with link to paper). I wanted to add some conceptual issues that we also tackle in the paper.
Paper drop, for anyone interested in #metascience, #statistics, or #metaanalysis! @clintin.bsky.social and I show in a new paper in JASA that the P-curve, a popular forensic meta-analysis method, has deeply undesirable statistical properties. www.tandfonline.com/doi/full/10.... 1/?
August 9, 2025 at 9:18 PM
New paper with @richarddmorey.bsky.social now out in JASA, where we critically examine p-curve. Below is Richard’s excellent summary of the many poor statistical properties of p-curve (with link to paper). I wanted to add some conceptual issues that we also tackle in the paper.
This week, I had the pleasure of teaching the Bayesian approach to network analysis at the Network Psychometrics summer school at Lake Como School of Advanced Studies.
Organized by Giulio Constantini, Michela Zambelli, and Semira Tagliabue with @briganti.bsky.social and @anastasiapsy.bsky.social…
Organized by Giulio Constantini, Michela Zambelli, and Semira Tagliabue with @briganti.bsky.social and @anastasiapsy.bsky.social…
August 8, 2025 at 3:12 PM
This week, I had the pleasure of teaching the Bayesian approach to network analysis at the Network Psychometrics summer school at Lake Como School of Advanced Studies.
Organized by Giulio Constantini, Michela Zambelli, and Semira Tagliabue with @briganti.bsky.social and @anastasiapsy.bsky.social…
Organized by Giulio Constantini, Michela Zambelli, and Semira Tagliabue with @briganti.bsky.social and @anastasiapsy.bsky.social…
Reposted by Maarten Marsman
Ben jij gedreven om psychische klachten te voorkomen voordat ze beginnen of terugkeren? Dan is dit promotietraject iets voor jou!
Shift Left @Arkin @amsterdamumc.bsky.social
lnkd.in/di4vWujy
@uvapsychology.bsky.social
Shift Left @Arkin @amsterdamumc.bsky.social
lnkd.in/di4vWujy
@uvapsychology.bsky.social
LinkedIn
This link will take you to a page that’s not on LinkedIn
lnkd.in
August 6, 2025 at 6:44 PM
Ben jij gedreven om psychische klachten te voorkomen voordat ze beginnen of terugkeren? Dan is dit promotietraject iets voor jou!
Shift Left @Arkin @amsterdamumc.bsky.social
lnkd.in/di4vWujy
@uvapsychology.bsky.social
Shift Left @Arkin @amsterdamumc.bsky.social
lnkd.in/di4vWujy
@uvapsychology.bsky.social
Reposted by Maarten Marsman
Hello world! We are a new company that provides support for organizations and industries who use the JASP open-source stats program. Check out our website www.jasp-services.com and our first blog post www.jasp-services.com/first-post/
Know companies using commercial stats software? Share this info!🙂
Know companies using commercial stats software? Share this info!🙂
Home - JASP Services BV
www.jasp-services.com
May 21, 2025 at 1:57 PM
Hello world! We are a new company that provides support for organizations and industries who use the JASP open-source stats program. Check out our website www.jasp-services.com and our first blog post www.jasp-services.com/first-post/
Know companies using commercial stats software? Share this info!🙂
Know companies using commercial stats software? Share this info!🙂
Reposted by Maarten Marsman
🚨 New preprint: A Stochastic Block Prior for Clustering in Graphical Models
We introduce an SBM prior to detect/test clusters in Bayesian network models for binary & ordinal data. Includes R code & tutorial.
📄 osf.io/preprints/ps...
📚 Blog: www.nikolasekulovski.com/blog/post2/
We introduce an SBM prior to detect/test clusters in Bayesian network models for binary & ordinal data. Includes R code & tutorial.
📄 osf.io/preprints/ps...
📚 Blog: www.nikolasekulovski.com/blog/post2/
OSF
osf.io
May 9, 2025 at 3:50 PM
🚨 New preprint: A Stochastic Block Prior for Clustering in Graphical Models
We introduce an SBM prior to detect/test clusters in Bayesian network models for binary & ordinal data. Includes R code & tutorial.
📄 osf.io/preprints/ps...
📚 Blog: www.nikolasekulovski.com/blog/post2/
We introduce an SBM prior to detect/test clusters in Bayesian network models for binary & ordinal data. Includes R code & tutorial.
📄 osf.io/preprints/ps...
📚 Blog: www.nikolasekulovski.com/blog/post2/
Reposted by Maarten Marsman
I am looking forward to expanding the scope of my professorship by combining cognitive and statistical modeling with LLMs😊
There will be two job openings for postdoc positions soon - one starting in September 2025 and another one a year later.
There will be two job openings for postdoc positions soon - one starting in September 2025 and another one a year later.
🚀 930.000 Euro für #Psychologie -Forschung: Prof. Daniel Heck nutzt #KI, um psychologische Theorien präziser zu machen. Mithilfe von #LLMs sollen unscharfe Begriffe in messbare Modelle übersetzt werden – ein Schritt zu besseren Experimenten & klareren Erkenntnissen #Forschung uni-marburg.de/gDNQIi
April 23, 2025 at 10:26 AM
I am looking forward to expanding the scope of my professorship by combining cognitive and statistical modeling with LLMs😊
There will be two job openings for postdoc positions soon - one starting in September 2025 and another one a year later.
There will be two job openings for postdoc positions soon - one starting in September 2025 and another one a year later.
I am excited to teach at the Summer School on Network Psychometrics this August in Como, Italy! Theory, methods, and hands-on R for analyzing cross-sectional and longitudinal data. Full information and application (deadline April 24th): ntps.lakecomoschool.org
Home - Network Psychometrics: theory, methods and applications
Network Psychometrics: Theory, Methods and Applications 4-8 August 2025 Join us to explore the forefront of psychological research! Network Psychometrics has rapidly gained prominence across various...
ntps.lakecomoschool.org
April 8, 2025 at 6:38 AM
I am excited to teach at the Summer School on Network Psychometrics this August in Como, Italy! Theory, methods, and hands-on R for analyzing cross-sectional and longitudinal data. Full information and application (deadline April 24th): ntps.lakecomoschool.org
Reposted by Maarten Marsman
My tutorial on Sequentual Monte Carlo for psychology and behavioural science is out now in Behavior Research Methods! Check it out at link.springer.com/article/10.3...
An introduction to Sequential Monte Carlo for Bayesian inference and model comparison—with examples for psychology and behavioral science - Behavior Research Methods
Bayesian inference is becoming an increasingly popular framework for statistics in the behavioral sciences. However, its application is hampered by its computational intractability – almost all Bayesi...
link.springer.com
March 26, 2025 at 3:42 PM
My tutorial on Sequentual Monte Carlo for psychology and behavioural science is out now in Behavior Research Methods! Check it out at link.springer.com/article/10.3...
Reposted by Maarten Marsman
Are psychometric networks sufficiently supported by data such that one can be confident when interpreting its results? We analysed 294 psychometric networks from 126 papers with the Bayesian approach to address this question @jmbh.bsky.social Sara Ruth van Holst @maartenmarsman.bsky.social 🧵
Statistical Evidence in Psychological Networks: A Bayesian Analysis of 294 Networks from 126 Studies: http://osf.io/62ydg/
January 24, 2025 at 11:02 AM
Are psychometric networks sufficiently supported by data such that one can be confident when interpreting its results? We analysed 294 psychometric networks from 126 papers with the Bayesian approach to address this question @jmbh.bsky.social Sara Ruth van Holst @maartenmarsman.bsky.social 🧵
Reposted by Maarten Marsman
Emotions are reactions to situations we encounter in daily life. In our new paper in Psych Review (psycnet.apa.org/fulltext/202...; with @oisinryan.bsky.social and @fdabl.bsky.social), we take a first step towards building a generative model for emotion dynamics based on this simple principle 1/4
January 7, 2025 at 9:19 AM
Emotions are reactions to situations we encounter in daily life. In our new paper in Psych Review (psycnet.apa.org/fulltext/202...; with @oisinryan.bsky.social and @fdabl.bsky.social), we take a first step towards building a generative model for emotion dynamics based on this simple principle 1/4
🚨 New pre-print alert! 🚨
We introduce a Bayesian independent samples t test for comparing networks of binary and ordinal Variables.
Curious why that matters for your next network analysis? 🧵
osf.io/preprints/os...
We introduce a Bayesian independent samples t test for comparing networks of binary and ordinal Variables.
Curious why that matters for your next network analysis? 🧵
osf.io/preprints/os...
OSF
osf.io
December 20, 2024 at 7:55 AM
🚨 New pre-print alert! 🚨
We introduce a Bayesian independent samples t test for comparing networks of binary and ordinal Variables.
Curious why that matters for your next network analysis? 🧵
osf.io/preprints/os...
We introduce a Bayesian independent samples t test for comparing networks of binary and ordinal Variables.
Curious why that matters for your next network analysis? 🧵
osf.io/preprints/os...
Reposted by Maarten Marsman
Do you need educational and psychological item response data to do your research? The IRW has 600 item response datasets (more coming!), distributed in a standardized format and ready for analysis.
December 10, 2024 at 5:39 PM
Do you need educational and psychological item response data to do your research? The IRW has 600 item response datasets (more coming!), distributed in a standardized format and ready for analysis.