A general formula (α) of which a special case is the Kuder-Richardson coefficient of equivalence is shown to be the mean of all split-half coefficients resulting from different splittings of a test. α is therefore an estimate of the correlation between two random samples of items from a universe of items like those in the test. α is found to be an appropriate index of equivalence and, except for very short tests, of the first-factor concentration in the test. Tests divisible into distinct subtests should be so divided before using the formula. The index
 
$$\bar r_{ij} $$

 , derived from α, is shown to be an index of inter-item homogeneity. Comparison is made to the Guttman and Loevinger approaches. Parallel split coefficients are shown to be unnecessary for tests of common types. In designing tests, maximum interpretability of scores is obtained by increasing the first-factor concentration in any separately-scored subtest and avoiding substantial group-factor clusters within a subtest. Scalability is not a requisite.

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Coefficient alpha and the internal structure of tests.

This paper presents a critique of expected utility theory as a descriptive model of decision making under risk, and develops an alternative model, called prospect theory. Choices among risky prospects exhibit several pervasive effects that are inconsistent with the basic tenets of utility theory. In particular, people underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty. This tendency, called the certainty effect, contributes to risk aversion in choices involving sure gains and to risk seeking in choices involving sure losses. In addition, people generally discard components that are shared by all prospects under consideration. This tendency, called the isolation effect, leads to inconsistent preferences when the same choice is presented in different forms. An alternative theory of choice is developed, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights. The value function is normally concave for gains, commonly convex for losses, and is generally steeper for losses than for gains. Decision weights are generally lower than the corresponding probabilities, except in the range of low prob- abilities. Overweighting of low probabilities may contribute to the attractiveness of both insurance and gambling. EXPECTED UTILITY THEORY has dominated the analysis of decision making under risk. It has been generally accepted as a normative model of rational choice (24), and widely applied as a descriptive model of economic behavior, e.g. (15, 4). Thus, it is assumed that all reasonable people would wish to obey the axioms of the theory (47, 36), and that most people actually do, most of the time. The present paper describes several classes of choice problems in which preferences systematically violate the axioms of expected utility theory. In the light of these observations we argue that utility theory, as it is commonly interpreted and applied, is not an adequate descriptive model and we propose an alternative account of choice under risk. 2. CRITIQUE

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Prospect theory: an analysis of decision under risk

A new method for automatic indexing and retrieval is described. The approach is to take advantage of implicit higher-order structure in the association of terms with documents (“semantic structure”) in order to improve the detection of relevant documents on the basis of terms found in queries. The particular technique used is singular-value decomposition, in which a large term by document matrix is decomposed into a set of ca. 100 orthogonal factors from which the original matrix can be approximated by linear combination. Documents are represented by ca. 100 item vectors of factor weights. Queries are represented as pseudo-document vectors formed from weighted combinations of terms, and documents with supra-threshold cosine values are returned. initial tests find this completely automatic method for retrieval to be promising.

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Indexing by Latent Semantic Analysis

(1966). The Scree Test For The Number Of Factors. Multivariate Behavioral Research: Vol. 1, No. 2, pp. 245-276.

The scree test for the number of factors

A Scaling Method for Priorities in Hierarchical Structures

A theory of data

Psychological scaling without a unit of measurement.

Single-Peaked Functions and the Theory of Preference.

Components of risk in decision making: Probability and variance preferences.

THE general acceptance of the multiple-choice type test item as the best one for objective measurement of aptitude or achievement does not imply that its merits are optimal. Any variation upon an already widely accepted and useful technique which indicates promise of improved measurement is deserving of further investigation. A response method3 for multiple-choice items which has certain theoretical advantages over the conventional response method is considered here, and this study is an empirical investigation of some of its relative merits. The conventional response method (C method) for multiplechoice items requires selecting and marking the answer from among the choices offered. In this study it was to pick one of four. The conventional item score in a power test is one point when the answer is chosen and zero when a distracter is chosen. Complete information leads to an item score of one and misinformation to a score of zero. Partial information may lead to a score of either one or zero. The inability of the

/pdf/the-assessment-of-partial-knowledge-4oufidbwj9.pdf

Clyde H. Coombs

Papers

A theory of data

Psychological scaling without a unit of measurement.

Single-Peaked Functions and the Theory of Preference.

Components of risk in decision making: Probability and variance preferences.

The assessment of partial knowledge