Category: Mariëlle

Small Samples

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.

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.

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.