Bibliometricians strive for linearity!

In library science, the goal is to discover a new, subtle but powerful linearity underlying the data. This is the world encountered by David Andrich and Michael Linacre when they presented Rasch-based papers at the Fourth International Conference on Bibliometrics, Informetrics and Scientometrics, held in Berlin, Germany in September 1993.

Dr. Hildrun Kretschmer, the force behind the Conference, discovered Rasch analysis during her visits to library scientists Abe Bookstein and Don Swanson at the University of Chicago. Our common concern for linear measures made us "birds of a feather who flock together" - a maxim that has become one of Dr. Kretschmer's guiding tenets!

Michael Linacre's paper recounted the importance of linearity in measurement and the principles underlying the Rasch model. Though the model itself was new to the audience, he soon found he was "preaching to the choir." For, ever since the work of Derek De Solla Price, library scientists have realized that it is only when trends and patterns in the data have been expressed in linear form, that the data can be understood or become the basis for prediction. Price did this with trends in the history of science. His findings (1961, 1963) have become scientific lore, e.g., "90% of all scientists who ever lived are alive today", together with concepts such as "invisible colleges".

David Andrich struck a resonant note with his warning that arbitrary combining or splitting of rating scale categories damages the measurement properties, and so the meaning, of the variable underlying the data. This accords with a dictum of the most influential library scientist, Eugene Garfield, originator of the Social Sciences Citation Index bibliographic database, "May we respectfully caution against the serious implication that quantitative data [counts and ratings] can be used without considered qualitative judgments" (Essays of an Information Scientist, Vol. 1, 1977, p.120).

Library scientists examine their data to discover underlying linear patterns in behavior such as book borrowing frequency, paper co-authorship recurrence, and journal citations. Their dedication in this endeavor is an object lesson yet to be learned by social scientists for whom the maxim "if it seems numerical, then it must be linear" suffices.

John Michael Linacre

Bibliometricians strive for linearity. Linacre JM. Rasch Measurement Transactions 1993 7:3 p.313


Bibliometricians strive for linearity. Linacre JM. … Rasch Measurement Transactions, 1993, 7:3 p.313

Please help with Standard Dataset 4: Andrich Rating Scale Model



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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