| Title | Date | Views | Brief Description |
|---|
| An Examination of the Residual Covariance Structures of Complex Performance Exercises Under Various Scaling and Scoring Methods |
2008 |
1225 |
Large-scale assessment programs are increasingly including complex performance exercises along with traditional multiple-choice items in a given test. These performance assessments are developed in part to measure sets of skills that are part of the ... |
| Modeling differential pacing trajectories in high stakes computer adaptive testing using hierarchical linear modeling and structural equation modeling |
2006 |
754 |
"This study compares two statistical methods for modeling changes in response latency (timing) patterns on a high-stakes adaptive test: (1) hierarchical linear modeling (HLM2) and (2) growth modeling using structural equation modeling (SEM). The test... |
| A comparison of traditional test blueprinting and item development to assessment engineering in a licensure context |
2010 |
1151 |
With the need for larger and larger banks of items to support adaptive
testing and to meet security concerns, large-scale item generation is a
requirement for many certification and licensure programs. As part of the mass
production of items, it i... |
| Conditions affecting the accuracy of classical equating methods for small samples under the NEAT design: a simulation study |
2011 |
741 |
Small sample equating remains a largely unexplored area of research. This study attempts to fill in some of the research gaps via a large-scale, IRT-based simulation study that evaluates the performance of seven small-sample equating methods under va... |
| Data collection design for equivalent groups equating:using a matrix stratification framework for mixed-format assessment |
2012 |
340 |
Mixed-format assessments are increasingly being used in large scale standardized assessments to measure a continuum of skills ranging from basic recall to higher order thinking skills. These assessments are usually comprised of a combination of (a) m... |