ABSTRACT
Item factor analysis plays an essential role in the development of tests or scales to measure behavioral tendencies that are considered to be a matter of degree but are observed only as discrete responses. Typical examples are:
Tests of school science achievement based on responses to a number of ◾ exercises marked right or wrong Social surveys in which degree of conservatism of the respondent is ◾ assessed by agreement or disagreement with positions on a variety of public issues Patient self-reports of satisfaction with the outcome of a medical treat-◾ ment rated on a 7-point scale Inventory of activities favorable or unfavorable to general health ◾ reported in terms of frequency: never, up to once a month, up to once a week, more than once a week Nutrition survey of food preference categorized as ◾ dislike very much, dislike moderately, neither like nor dislike, like moderately, like very much
The main problem in constructing these kinds of response instruments is the lack of any definite rules for choosing items that best represent the concept to be measured. The content and wording of items that embody the concept are almost always up to the item writer. Once the instrument is administered to respondents of interest, however, data become available for critical item-by-item examination of their suitability as representatives of the concept. The unique contribution of item factor analysis lies in its power to reveal whether the patterns of association among the item responses arise from one dimension of measurement or more than one.
