Scientific Theories and Empirical Problems

"Science does not, so far as we know, produce theories which are true or even highly probable. Although rare, it sometimes happens that a theory exactly predicts an experimental outcome. When that desirable result is achieved, there is cause for general rejoicing. It is far more common for the predictions deduced from a theory to come close to reproducing the data which constitute a specific problem, but with no exact coincidence of results. ... Empirical problems are frequently solved because, for problem solving purposes, we do not require an exact, but only an approximate, resemblance between theoretical results and experimental ones."
Larry Laudan, Progress and its Problems. Berkeley, CA: University of California Press, 1977, pp. 23, 224

"Essentially, all models are wrong, but some are useful."
Box, G. E. P., and Draper, N. R., (1987), Empirical Model Building and Response Surfaces, John Wiley & Sons, New York, NY.


The Essential Conditions of Measurement

"Measurement appears to require that three conditions be met. The first of these conditions is that one have a working concept of the character to be measured. A psychologist needs a clear notion of what intelligence is before he constructs a test to measure it. Binet, for example, struggled for some years to get an idea of the character he ought to be trying to measure. The crystallization of a clear concept of what one desires to measure is often a critical point in the development of a field of research. In early work, the concept must almost necessarily be vague and nebulous, representing a sort of groping for something that will satisfy a certain purpose. The measurements resulting from such a concept naturally contain an abundance of spurious elements. The cultivation and delimitation of a valid concept of a critical variable is in itself an important contribution to measurement.

"The second necessary condition of measurement is a satisfactory representation of the character to be measured, in the amount that is exhibited by the phenomenon [e.g., student ability]. By a satisfactory representation, we mean one that is perceptible, accurate, and convenient. In some cases, this is equivalent to saying that, for characteristics which are not directly perceptible, an objectifying function or agent [e.g., a test item] must be found.

"This brings us to our third condition for measurement, which is a basis for quantitative comparison. Measurement is essentially a "more-than" or "less- than" type of comparison between a reference point (usually a mark on a scale) and the phenomenon. Measurement in terms of units which are equal, fixed, and standardized, is of course ordinarily to be preferred where it is possible. In the first place, such measurements can be readily recorded and transmitted to others. In the second place, they ordinarily convey more significance to a larger number of people than do unequal units, or values having special significance because of certain unique experiences connected with them. In the third place, they facilitate - in fact they make possible - quantitative science, with its many interrelations, expressed as laws and functions. To utilize units which do not correspond to our number system (in the sense of equal increments) would be to inject hopeless confusion into problems that are at best baffling."

Douglas E. Scates, excerpted from Psychometrika, March 1937, Vol. 2, No.1, p. 27-34.


"G. Rasch's Probabilistic Models.. book represents an attempt to create new paths for scientific behavioral statistics which, till now, have confused groups with individuals... We encourage as many people as possible to obtain and read the book."
from a 1962 review by Sven Rydberg, University of Stockholm, Nordisk Psykologi, 14(7), p.347-8.


RMT 7:3 Quotations and Notations. … Rasch Measurement Transactions, 1993, 7:3 p.312ff.



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

To be emailed about new material on www.rasch.org
please enter your email address here:

I want to Subscribe: & click below
I want to Unsubscribe: & click below

Please set your SPAM filter to accept emails from Rasch.org

www.rasch.org welcomes your comments:

Your email address (if you want us to reply):

 

ForumRasch Measurement Forum to discuss any Rasch-related topic

Go to Top of Page
Go to index of all Rasch Measurement Transactions
AERA members: Join the Rasch Measurement SIG and receive the printed version of RMT
Some back issues of RMT are available as bound volumes
Subscribe to Journal of Applied Measurement

Go to Institute for Objective Measurement Home Page. The Rasch Measurement SIG (AERA) thanks the Institute for Objective Measurement for inviting the publication of Rasch Measurement Transactions on the Institute's website, www.rasch.org.

Coming Rasch-related Events
May 17 - June 21, 2024, Fri.-Fri. On-line workshop: Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com
June 12 - 14, 2024, Wed.-Fri. 1st Scandinavian Applied Measurement Conference, Kristianstad University, Kristianstad, Sweden http://www.hkr.se/samc2024
June 21 - July 19, 2024, Fri.-Fri. On-line workshop: Rasch Measurement - Further Topics (E. Smith, Winsteps), www.statistics.com
Aug. 5 - Aug. 6, 2024, Fri.-Fri. 2024 Inaugural Conference of the Society for the Study of Measurement (Berkeley, CA), Call for Proposals
Aug. 9 - Sept. 6, 2024, Fri.-Fri. On-line workshop: Many-Facet Rasch Measurement (E. Smith, Facets), www.statistics.com
Oct. 4 - Nov. 8, 2024, Fri.-Fri. On-line workshop: Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com
Jan. 17 - Feb. 21, 2025, Fri.-Fri. On-line workshop: Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com
May 16 - June 20, 2025, Fri.-Fri. On-line workshop: Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com
June 20 - July 18, 2025, Fri.-Fri. On-line workshop: Rasch Measurement - Further Topics (E. Smith, Facets), www.statistics.com
Oct. 3 - Nov. 7, 2025, Fri.-Fri. On-line workshop: Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com

 

The URL of this page is rasch.org/rmt/rmt73p.htm

Website: www.rasch.org/rmt/contents.htm