Review of RASCAL Program

RASCAL (Version 3.5) is a one-parameter logistic model item calibration and test scoring program in the Assessment Subsystem of the MicroCAT Testing System Program (Assessment Systems Corporation, 1989). The software package runs on a PC, requires DOS 2.0 or higher, 320 KB RAM (at least), and two diskette drives (or one diskette and a hard drive). It uses the unconditional maximum-likelihood (JMLE) calibration method to estimate item difficulty parameters. Correction for the bias in the unconditional ML estimates is an option. The scaling factor (D) may be set to 1.7 to produce results comparable to the results produced by programs such as LOGIST or BILOG, or set to 1.0 to produce results on similar scales to the results obtained with programs such as BICAL, BIGSTEPS or Facets. With D=1.7, ability scores are scaled to a mean and standard deviation of 0.0 and 1.0 respectively. With D=1, the mean item difficulty is scaled to a value of 0.0. The facility to link RASCAL item and ability parameter estimates to the scales used in other programs is a useful feature.

RASCAL provides the option of fixing the values for some of the items. This means that these items function like an anchor test so that the remaining items can be linked to the scale on which the anchor items are placed.

RASCAL provides the following output: (1) item difficulty parameter estimates and associated asymptotic standard errors; (2) item goodness of fit statistics; (3) a number-correct score to maximum-likelihood ability score conversion table with standard errors of ability estimation, percentiles, and scaled scores; and (4) graphical representations of the distributions of item difficulties and examinee ability scores (called "item by persons map"), the test characteristic function, and the test information function. The item by persons map is especially helpful because the map (or graph): (a) reminds users that items and persons are reported on the same scale, (b) provides the conjoint distributions of ability and item parameter estimates, and (c) allows user judgments about the appropriateness of the test items for providing optimal measurements with the examinee sample.

Program documentation is clear and provides the user with complete information for installing, running the program in the interactive mode, and interpreting the results from a listing of some useful program outputs. The user interface is friendly, providing well- spaced and organized input. Information is provided on screen throughout the estimation process. The program is easy to use and quick to run. Item deletion is also easy to accomplish.

One limitation concerns the listing of the input files. After the program is started, if the user does not remember the name of the input file when requested, he/she needs to get back to DOS to get the name of the file and then he/she must start over again. The quality of graphics in the output display could be improved. The output listing would be enhanced if item information function graphs were included. These graphs supply the user with the amount of information provided by individual test items. Finally, scoring omits and not- reached items as zero may be a problem with some testing applications.

The software developers of RASCAL have done a fine job of preparing a software program that can handle dichotomously scored data, with documentation that is well-written and informative. The limitations we noted are minor, but should be considered in the next update.

Assessment Systems Corporation. 1989. User's manual for the MicroCAT Testing System (3rd Ed.). St. Paul, MN: Author.

Review of RASCAL Program, R Hambleton & P Narayanan … Rasch Measurement Transactions, 1992, 6:3 p. 236

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Rasch Measurement Transactions (free, online) Rasch Measurement research papers (free, online) Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch Applying the Rasch Model 3rd. Ed., Bond & Fox Best Test Design, Wright & Stone
Rating Scale Analysis, Wright & Masters Introduction to Rasch Measurement, E. Smith & R. Smith Introduction to Many-Facet Rasch Measurement, Thomas Eckes Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr. Statistical Analyses for Language Testers, Rita Green
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar Journal of Applied Measurement Rasch models for measurement, David Andrich Constructing Measures, Mark Wilson Rasch Analysis in the Human Sciences, Boone, Stave, Yale
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