The Rasch Model derived from E.L. Thorndike's (1904) Criteria

Edward Lee Thorndike (1904) criticizes a pioneering 1895 spelling test of Dr. Joseph M. Rice, because its words are of unequal difficulty (p. 8, see below). "In arranging a scale of measurement one must as far as possible, (1) keep free of individual opinion, ... (2) call equal only those things which can be interchanged without making any difference to the issue involved." (p. 14-15, italics Thorndike's). This suggests that, at the time, Thorndike considered that the measurement of ability could only be performed by ascertaining the level of success on a set of equally difficult items. Though Thorndike's later writings relax this requirement, let us derive a measurement model from his 1904 criteria.

Imagine that Dr. Rice compiles a set {i} of spelling-word items all of equal difficulty d_i, and Prof. Thorndike another set {j} all of equal difficulty d_j. Both sets are administered to examinee n of ability b_n and to examinee m of ability b_m.

We observe that examinee n has F_ni successes and F_in failures on item set {i}. So the empirical odds of success for examinee n on item set {i} are F_ni/F_in. From this, we infer that examinees of ability b_n, such as examinee n, have P_ni/P_in odds of success on items of difficulty d_i, such as item set {i}, where

and f is the relationship between b_n and d_i yielding these odds.

Similarly, when examinee m encounters item set {i}:

The ability difference between m and n is indicated by their relative odds of success on item set {i}:

and g is the relationship between b_n, b_m and d_i yielding these odds.

The same holds true when examinees n and m encounter item set {j}:

and their relative odds of success are

Thorndike's first criterion is that measures must be free of individual opinion, i.e., of who chooses the spelling-word test items. Accordingly, for invariance in measuring ability differences, the ability difference between b_n and b_m must be independent of the item set. Therefore it must be the same for items sets {i} and {j}. Consequently,

Rearranging,

We can choose item set {j} to have any difficulty, in particular that of item "0" at the local origin of the scale, i.e., of difficulty d_j=d₀. Also the ability of examinee n must be independent of the particularly ability of examine m, so we can also choose m to be examinee "0" whose ability is at the local origin of the scale, b_j=b₀. The local origins of the ability and difficulty scales can be constructed to coincide, so that the probability of success of examinee "0" on item "0" becomes 0.5.

so that

P_n0/P_0n is the odds of success of an examinee of ability of b_n on a standard item at the local origin of the scale. Let this be the definition of b_n. Similarly, (P_i0/P_0i) is the odds of failure on an item of difficulty d_i by a standard examinee at the local origin of the scale. Let this be the definition of d_i. Then

f(b_n,d_i) = (P_ni/P_in) = (P_n0/P_0n) / (P_i0/P_0i) = b_n / d_i

yielding the ratio form of the Rasch model:

P_ni/P_in = b_n / d_i

and

g(b_n,b_m) = g(b_n,b_m,d_i) = (P_ni/P_in)/(P_mi/P_im)

= (b_n/d_i)/(b_m/d_i) = b_n/b_m

In a ratio metric, the odds of success of examinee n on item i is the ability of examinee n divided by the difficulty of item i. Expressing f(b_n,d_i) in a more convenient additive metric, and reparameterizing, we obtain the familiar form of the dichotomous Rasch model:

where B_n and D_i are ability and difficulty expressed in an additive metric. Thus, E. L. Thorndike's 1904 criteria lead to the Rasch model.

And the difference in ability between m and n is B_m - B_n ≈ log(F_mi/F_im) - log(F_ni/F_in) ≈ log(F_mj/F_jm) - log(F_nj/F_jn)

John Michael Linacre

Thorndike, E.L. (1904). An introduction to the theory of mental and social measurements. New York: Teacher's College.

Excerpts from Thorndike, E. (1904). Introduction to the theory of mental measurement. New York: Science Press (pp. 5-6):

The Special Problems of Mental Measurements

In the mental sciences, as in the physical, we have to measure things, differences, changes and relations. The psychologist thus measures the acuity of vision, the changes in it due to age, and the relation between acuity of vision and ability to learn to spell. The economist thus measures the wealth of a community, the changes due to certain inventions and perhaps the dependence or the wealth of communities upon their tariff laws or labor laws or poor laws. Such measurements, which involve human capacities and acts, are subject to certain special difficulties, due chiefly to the absence or imperfection of units in which to measure, the lack of constancy in the facts measured, and the extreme complexity of the measurements to be made.

lf, for instance, one attempts to measure even so simple a fact as the spelling ability of ten-year-old boys, one is hampered at the start by the fact that there exist no units in which to measure. One may, of course, arbitrarily make up a list of 10 or 50 or 100 words and measure ability by the number spelled correctly. But if one examines such a list, for instance the one used by Dr. J. M. Rice in his measurements of the spelling ability of 18,000 children, one is or should be at once struck by the inequality of the units. Is 'to spell certainly correctly' equal to 'to spell because correctly'? In point of fact, I find that of a group of about 120 children, 30 missed the former and only one the latter. All of Dr. Rice's results which are based on the equality of any one of his 50 words with any other of the 50 are necessarily inaccurate, ....

The problem for a quantitative study of the mental sciences is thus to devise means of measuring things, differences, changes and relationships for which standard units of amount are often not at hand, which are variable, and so unexpressible in any case by a single figure, and which are so complex that to represent any one of them a long statement in terms of different sorts of quantities is commonly needed. This last difficulty of mental measurements is not, however, one which demands any form of statistical procedure essentially different from that used in science in general.

The Rasch Model derived from E. L. Thorndike's 1904 Criteria. Thorndike, E.L.; Linacre, J.M. … Rasch Measurement Transactions, 2000, 14:3 p.763

1. The Rasch Model derived from E. L. Thorndike's 1904 Criteria, Thorndike, E.L.; Linacre, J.M. … 2000, 14:3 p.763
2. Rasch model derived from consistent stochastic Guttman ordering, Roskam EE, Jansen PGW. … 6:3 p.232
3. Rasch model derived from Counts of Right and Wrong Answers, Wright BD. … 6:2 p.219
4. Rasch model derived from counting right answers: raw Scores as sufficient statistics, Wright BD. … 1989, 3:2 p.62
5. Rasch model derived from Thurstone's scaling requirements, Wright B.D. … 1988, 2:1 p. 13-4.
6. Rasch model derived from Campbell concatenation: additivity, interval scaling, Wright B.D. … 1988, 2:1 p. 16.
7. Dichotomous Rasch model derived from specific objectivity, Wright BD, Linacre JM. … 1987, 1:1 p.5-6

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
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