Carol A. Nickerson

Scaling distortion in numerical conjoint measurement

Proponents of numerical conjoint measurement gen erally assume that the techniques goodness-of-fit mea sure will detect an inappropriate composition rule or the presence of random response error. In this paper a number of hypothetical and real preference rank order ings are analyzed using both axiomatic conjoint mea surement and numerical conjoint measurement to dem onstrate that this assumption is not warranted and may result in a distorted scaling.

DETERMINING THE IMPACT OF SEX PREFERENCES ON FERTILITY: A DEMONSTRATION STUDY

The stopping rule measure of sex preferences represents a combination of psychological measures of preference and behavioral intentions. This study of 172 college students demonstrates that the stopping rule measure is a useful and practical method of measuring sex preferences. The results further indicate that parity progression ratio measures inherently underestimate the effect of sex preferences on individual fertility because they incorrectly assume that sex preferences (a) are homogeneous within the population and (b) can only act to increase, not to decrease, fertility. Use of the stopping rule measure to predict the possible effects of sex preselection techniques on fertility is also discussed.

Extended axiomatic conjoint measurement: A solution to a methodological problem in studying fertility-related behaviors

This paper has three purposes: (1) to develop a methodology based on axiomatic conjoint measure ment to accompany the McClelland (1980) fertility de cision-making model; (2) to demonstrate the use of the methodology by applying it to the study of a specific fertility-related behavior (contraceptive choice); and (3) to evaluate the usefulness and validity of the model and its methodology for studying fertility-re lated behaviors. The within-persons methodology de veloped is contrasted with the across-persons method ology customarily used to test expectancy-value models of behavior. Index terms: Conjoint mea surement, Contraception, Decision making, Expec tancy-value models, Preference models, Within-per sons analysis.

The University Of Colorado Meaning Norms

There exist surprisingly few normative lists of word meanings even though homographs—words having single spellings but two or more distinct meanings—are useful in studying memory and language. The meaning norms that are available all have one or more weaknesses, including: (1) the collection of free associates rather than meanings as responses to the stimulus words; (2) the collection of single rather than multiple responses to the stimulus words; (3) the inclusion of only the two most frequently occurring meaning categories, rather than all meaning categories, for the stimulus words; (4) omission of the responses typical of each meaning category; (5) inadequate randomization of the presentation order of the stimulus words; and (6) unpaced presentation of the stimulus words. We have compiled meaning norms for 90 common English words of low, medium, and high concreteness using a methodology designed to correct these weaknesses. Analysis showed that words of medium concreteness have significantly more first-response meanings than do words of either low or high concreteness, lending support to the view that concreteness is a categorical, rather than a continuous, semantic attribute.

Solutions to some problems in the implementation of conjoint analysis

Methodological problems encountered in implementing conjoint analysis include (1) the impractically large set of multiattribute choice alternatives created by the factorial combination of more than a few attributes, (2) the hypothetical nature of the alternatives in the choice set, and (3) the assumption that each individual’s preferences can be described by the same composition rule. The techniques of tailoring, belief matching, and axiom testing are suggested as solutions to these problems, and their use is demonstrated in a conjoint analysis study of individuals’ contraceptive preferences. It is noted that tailoring and belief matching can also be used as methodological enhancements in functional measurement studies.