Just Accepted: Guidelines to construct informative priors
The current paper demonstrates the usefulness of Bayesian estimation with small samples. In Bayesian estimation, prior information can be included. Prior information is information about the model parameters that originates from sources other than the data at hand. These sources can be literature, experts, or general knowledge. Including prior…
Researchers often have difficulties collecting enough data to obtain statistical power: when target groups are small (e.g., children with severe burn injuries), hard to access (e.g., infants of drug-dependent mothers), or measuring the participants requires prohibitive costs (e.g., measuring phonological difficulties of babies). Such obstacles to collecting data usually leads to a limited data set. Researchers can overcome this through simplifying their hypotheses and statistical models. However, this strategy is undesirable since the intended research question cannot be answered in this way.
APS symposium accepted: “Experts and Animals: How Can They Help Us?”
How and to what extend can we use the unique information derived from experts and animals? We discuss how expert opinions can be formalized and included in analyses, how animal studies can provide insight into human behavior, and ways to compare results from these sources…
Expert Data (Dis)agreement
Elicitation is the process of extracting knowledge about the parameters in the statistical model. This information can then be used to provide input for the prior distribution needed for Bayesian analysis. Several methods of prior elicitation are used in practice including the use of experts.
Livingroom of Science
Science is a dynamic process with continuously developing, often implicit rules and attitudes. Proclamations such as “this is how we always do it”, “get used to it”, or “this is what it takes to grow in academia” occur more frequently than they ideally should.
Application and Evaluation of an Expert Judgment Elicitation Procedure for Correlations
The purpose of the current study was to apply and evaluate a procedure to elicit expert judgments about correlations, and to update this information with empirical data. The result is a face-to-face group elicitation procedure with as its central element a trial roulette question that elicits experts’ judgments expressed as distributions.
How to handle missing data: A comparison of different approaches
Many researchers face the problem of missing data in longitudinal research. Especially, high risk samples are characterized by missing data which can complicate analyses and the interpretation of results.
Analyzing small data sets using Bayesian estimation: the case of posttraumatic stress symptoms following mechanical ventilation in burn survivors
The analysis of small data sets in longitudinal studies can lead to power issues and often suffers from biased parameter values. These issues can be solved by using Bayesian estimation in conjunction with informative prior distributions.