HSR Reports (1995) Profile: William P. Fisher, Jr. on Rasch Measurement

William P. Fisher, Jr., Ph.D., specializes in tailoring quantitative and qualitative health information systems to particular practice environments for use in clinical research and practice, utilization management, quality assessment and improvement, patient education, preventative medicine, treatment planning, health economics, and marketing.

What if you and a colleague in another institution were measuring patients' health signs using different instruments? Until recently, comparing the scores from the two patient groups would have been analogous to comparing apples and oranges, making bench-marking impossible. New mathematical modeling techniques are transforming rating scale, assessment, and test-based measurement. Probabilistic models originally developed by the Danish mathematician Georg Rasch, and extended and refined by the University of Chicago's Benjamin D. Wright, offer substantive improvements over currently popular methods of instrument validation.

Imagine easily being able to compare results of two studies that have used different measuring scales, or testing the reliability of a health status measurement tool much more efficiently than ever before! In addition to expediting the above, Rasch measurement constructs:
* equal interval units of measurement for statistical comparison;
* expression of scale values of survey/test items and people's health/abilities/attitudes in the same quantitative unit;
* individual scale value, error, and data quality estimates (model fit statistics) for each item and person;
* no problem with missing data;
* increased data quality;
* decreased data volume;
* validity assessment and reliability study built into analysis;
* the resources required to design self-scoring report forms that combine the rating worksheet with the measurement analysis for instant, on-the-spot qualitative analysis and quantitative results, obviating the need for expensive and time-consuming computerization;
* multi-faceted models that adjust measures for uncontrolled variations in judges' perceptions of, or environmental effects on health and performance;
* computer-, clinician-, or self-adaptive administration of instruments, which increases measurement efficiency by posing only the questions relevant to the patient; and
* the co-calibration (equating) of alternative instruments intended to measure the same construct, making it possible for them to measure in the same unit, even if they have different numbers of items, or are based on different observational frameworks, such as clinical examination, performance assessment, or patient self-report.

Abstracted with permission from HSR REPORTS, A Newsletter from the Department of Health Systems, Research & Public Health, Louisiana State University, School of Medicine in New Orleans, July 1995, Vol 1, No. 1.

HSR Reports (1995) Profile: William P. Fisher, Jr. on Rasch measurement. Fisher WP Jr. … Rasch Measurement Transactions, 1995, 9:2 p.427

Rasch Publications
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
in Spanish: Análisis de Rasch para todos, Agustín Tristán Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez

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