QSG this week features a talk by Dani Rebouças. The title of the talk is “Bayesian Estimation of the Lognormal Model for Response Time Data“. The abstract for the talk is given below.
Bayesian Estimation of the Lognormal Model for Response Time Data by Dani Rebouças.
With the widespread of computerized assessments, item-level response times of tests and surveys have become increasingly available. Information derived from analyzing response time data may assist test administrators define an appropriate assessment length, and detect abnormal response behavior due to lack of motivation in psychological survey data (Schnipke and Scrams, 1997). Although increasing in popularity, previous applications of the log-normal model assume the item parameters and to be known. In reality, estimates of item parameters for such model are seldom available. In this study, we aim to evaluate model parameter estimates bias and precision obtained through Bayesian estimation when the item parameters are not available, and the effect of using item parameters point estimates from previous administrations (when those are available) on the estimation of the latent trait variable. Recommendations are provided for required sample size and test length for estimating the log-normal model parameters in the Bayesian framework.
QSG meets on Thursdays from 3:30-4:45pm in Corbett 378. All are welcome, and we hope to see you there.
The primary objective of this class is to provide students the opportunity to develop their critical thinking skills, presentation abilities, and knowledge of the most recent developments in quantitative and statistical methods and techniques. The seminar format of this course is designed to stimulate and foster the intellectual environment of the program and department as well as to engage students at all levels. This is one of the required courses for non-quantitative students to get their minor in quantitative psychology. Quant minor requirements: https://psychology.nd.edu/graduate-programs/areas-of-study/quantitative/minor/