Here - Tilburg University

The aim of this study therefore is to compare these packages with respect to
parameter estimates and user friendliness.
Method and results
Datasets were simulated under several conditions with variation in the number
of participants. Results from multilevel IRT analyses in different software
packages are compared on their precision of estimating parameters, and the
time and number of iterations needed for convergence. We started our analysis
in GLLAMM (Stata) and as expected we found that the bias of the estimated
parameters was smaller in the n = 500 condition than in the n = 150 condition.
The time for convergence varied a lot between these different conditions, 1.5
hours and 30 minutes respectively. Our results indicate that using data with a
larger number of participants gives better estimates of the parameters, although
the time until convergence increases. The results indicate an underestimate of
the true parameters in all conditions. We will present a comparison of these
results with the performance of other software packages.
Keywords: bias, multilevel IRT, simulation, longitudinal, ordinal, quality of life.