Adaptive testing for psychological assessment: how many items are enough to run an adaptive testing algorithm?

Although the principles of adaptive testing were established in the psychometric literature many years ago (e.g., Weiss, 1977), and practice of adaptive testing is established in educational assessment, it not yet widespread in psychological assessment. One obstacle to adaptive psychological testing is a lack of clarity about the necessary number of items to run an adaptive algorithm. The study explores the relationship between item bank size, test length and measurement precision. Simulated adaptive test runs (allowing a maximum of 30 items per person) out of an item bank with 10 items per ability level (covering .5 logits, 150 items total) yield a standard error of measurement (SEM) of .47 (.39) after an average of 20 (29) items for 85-93% (64-82%) of the simulated rectangular sample. Expanding the bank to 20 items per level (300 items total) did not improve the algorithm's performance significantly. With a small item bank (5 items per ability level, 75 items total) it is possible to reach the same SEM as with a conventional test, but with fewer items or a better SEM with the same number of items.

Conception and construction of a Rasch-scaled measure for self-confidence in one's vocabulary ability.

Although different theoretical approaches indicate the importance of self-confidence in one's ability in educational or counselling psychology, there are only a few standardized psychological instruments, these being mainly questionnaires, that focus on this construct. The idea pursued is to expand a traditional ability test and create an objective personality measure for self-confidence in one's ability. Empirical evidence will be provided as to whether it is possible to construct and cross validate this measure using the Rasch model. A two step procedure allowing for a self rating of one's knowledge of words was designed using 25 items from a general knowledge - vocabulary test. The results indicate that it is possible to construct and cross validate a measure for self-confidence in one's ability using the Rasch model. Additionally, it is shown that the measure for self-confidence in one's ability is independent from the general knowledge.

The Mixed-Rasch Model: an example for analyzing the meaning of response latencies in a personality questionnaire.

The present study uses the Mixed-Rasch Model to analyze questionnaire data. It is hypothesized that more than one latent sub-population (classes) can be identified. It is also hypothesized that response latencies and social desirability can be used to describe and discriminate the latent classes. Using the software WinMira 2001, data from the Eysenck-Personality-Profiler-German-version (EPP-D) was analyzed. A so-called non-scaleable and a scaleable group of subjects were identified which differed with regard to the use of one response category, I don't know. However, there was no difference between these groups with regard to response latencies and social desirability. Results will be discussed with regard to the EPP-D scoring scheme as suggested in the manual.