A Technique for Improving Cumulative Scales.

This paper introduces a simple new procedure for obtaining a cumulative-type scale which should have properties of high reproducibility, high test-retest reliability and high stability from sample to sample in rank order of cutting points. Moreover, none of these properties need be obtained at the c...

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Bibliographic Details
Published in:Public Opinion Quarterly Vol. 16; no. 2; pp. 273 - 292
Main Authors: Stouffer, Samuel A., Borgatta, Edgar F., Hays, David G., Henry, Andrew F.
Format: Article
Published: Oxford University Press / USA Summer52
Subjects:
Online Access:View this record in EBSCOhost
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        10.1086/266388
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        atl: A Technique for Improving Cumulative Scales.
      aug:
        au:
          Stouffer, Samuel A.
          Borgatta, Edgar F.
          Hays, David G.
          Henry, Andrew F.
        affil:
          Professor of Sociology, Harvard University.
          Director of the Laboratory of Social Relations, Harvard University.
          Research Associate, Laboratory of Social Relations.
          Research Assistants, Laboratory of Social Relations.
      su:
        Sampling (Process)
        Scalability
        Reliability (Personality trait)
        Standards
        Dimensions
        Errors
      sug:
        subj:
          Sampling (Process)
          Scalability
          Reliability (Personality trait)
          Standards
          Dimensions
          Errors
      ab: This paper introduces a simple new procedure for obtaining a cumulative-type scale which should have properties of high reproducibility, high test-retest reliability and high stability from sample to sample in rank order of cutting points. Moreover, none of these properties need be obtained at the cost of restricting the scale to content of too narrowly limited specificity or to questions with too uniform a format. This new procedure is called the H-technique. The method simply consists of determining a given cutting point in a Guttman or Lazarsfeld latent distance scale not by means of a single response but rather by means of several responses, which are formed into a new contrived item. The objective is to maximize the information available from the basic data and hence to strengthen confidence in the scalability of the area under consideration and the generality of the dimension which the scale is defining and to improve the ranking of individuals through reduction of scale error.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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