Bayesian statistics and modelling
Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowledge about parameters in a …
A prospective, randomized, single-blinded, crossover trial to investigate the effect of a wearable device in addition to a daily symptom diary for the remote early detection of SARS-CoV-2 infections (COVID-RED)
It is currently thought that most—but not all—individuals infected with SARS-CoV-2 develop symptoms, but that the infectious period …
Generalized Linear Randomized Response Modeling using GLMMRR
Randomized response (RR) designs are used to collect response data about sensitive behaviors (e.g., criminal behavior, sexual desires). …
Speech discrimination in infants at family risk of dyslexia. Group and individual-based analyses
Deficiencies in discriminating and identifying speech sounds have been widely attested in individuals with dyslexia as well as in young …
Systematically Defined Informative Priors in Bayesian Estimation. An Empirical Application on the Transmission of Internalizing Symptoms Through Mother-Adolescent Interaction Behavior
Background. Bayesian estimation with informative priors permits updating previous findings with new data, thus generating cumulative …
The Data Representativeness Criterion. Predicting the Performance of Supervised Classification Based on Data Set Similarity.
In a broad range of fields it may be desirable to reuse a supervised classification algorithm and apply it to a new data set. However, …
Expert Elicitation for Latent Growth Curve Models. The Case of Posttraumatic Stress Symptoms Development in Children With Burn Injuries
Experts provide an alternative source of information to classical data collection methods such as surveys. They can provide additional …
A Tutorial on Using The Wambs Checklist to Avoid The Misuse of Bayesian Statistics
This chapter guides readers through the steps of the When-to-Worry-and-How-to-Avoid-the-Misuse-of-Bayesian-Statistics checklist (the …
The Importance of Collaboration in Bayesian Analyses with Small Samples
This chapter addresses Bayesian estimation with (weakly) informative priors as a solution for small sample size issues. Special …
A step forward. Bayesian hierarchical modelling as a tool in assessment of individual discrimination performance
Individual assessment of infants’ speech discrimination is of great value for studies of language development that seek to relate …
Standard Errors, Priors, and Bridge Sampling. A Discussion of Liu et al.
Liu, Hu, Cao, Wang, and Chen (2019) present five methods to estimate the marginal likelihood of Item Response Theory (IRT) models and …
Meta analysis of the outcomes of treatment of internal carotid artery near occlusion
Background. Guidelines recommend treating patients with an internal carotid artery near occlusion (ICANO) with best medical therapy …
Generalized Linear Mixed Models for Randomized Responses
Response bias (nonresponse and social desirability bias) is one of the main concerns when asking sensitive questions about behavior and …
Using the Data Agreement Criterion to Rank Experts' Beliefs
Experts’ beliefs embody a present state of knowledge. It is desirable to take this knowledge into account when making decisions. …
Proposal for a Five-Step Method to Elicit Expert Judgment
Elicitation is a commonly used tool to extract viable information from experts. The information that is held by the expert is extracted …
