Showing 1 - 4 of 4
For analyzing item response data, item response theory (IRT) models treat the discrete responses to the items as driven by underlying continuous latent traits, and consider the form of conditional probability of the response to each item given the latent traits. In a similar fashion, log-linear...
Persistent link: https://www.econbiz.de/10009477625
The item response times (RTs) collected from computerized testing represent an underutilized type of information about items and examinees. In addition to knowing the examinees’ responses to each item, we can investigate the amount of time examinees spend on each item. Current models for RTs...
Persistent link: https://www.econbiz.de/10010739189
Chapter 1 is concerned with confidence interval construction for the mean of a long-range dependent time series. It is well known that the moving block bootstrap method produces an inconsistent estimator of thedistribution of the normalized sample mean when its limiting distribution is not...
Persistent link: https://www.econbiz.de/10009477845
The simultaneous and nonparametric estimation of latent abilities and item characteristic curves is considered. In particular, the joint asymptotic properties of ordinal ability estimation and kernel smoothed nonparametric item characteristic curve estimation is investigated under relatively...
Persistent link: https://www.econbiz.de/10009477873