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Books > Science & Math > Mathematics > Applied > Probability & Statistics > 080392741X
  1. Rasch Models for Measurement (Quantitative Applications in the Social Sciences)
    Rasch Models for Measurement (Quantitative Applications in the Social Sciences)
    Rasch Models for Measurement (Quantitative Applications in the Social Sciences)
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  2. Rasch Models for Measurement (Quantitative Applications in the Social Sciences)

    Delivery: 10-20 Working Days
    Customer Ratings (1 reviews)
    Price R542.00

Additional Information

Measurement models developed by Georg Rasch are renowned in the social sciences. In this introduction, the focus is on the simple logistic model, which is one of the most elementary and commonly used. The author explains the general principles behind the models, and demonstrates their procedures for measurement. Comparisons are made with other more widely-used models. Throughout the text, an example from a personality inventory is used to provide continuity as the statistical arguments are presented and procedures explained.

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David Andrich
Brand: SAGE Publications, Inc
Used Book in Good Condition
SAGE Publications, Inc
SAGE Publications, Inc
SAGE Publications, Inc
SAGE Publications, Inc
Most Helpful Customer Reviews

Statistical Methodology for Nominative-Ordinal Analysis scoring surveys. Part of a set of the series "Quantitative Applications in the Social Sciences." The title of the series gives a false impression that this is a sociological text or method but it is widely used in health care and in opinion surveys. This is a "must have" for the statistician. The methodolgy most interesting to me is giving nominative ordinal responses a numerical value and the method for measuring the fit of your measure to assure that you are measuring the factor intended to be measured. The Rasch model is a model in the sense that it represents the structure which data should exhibit in order to obtain measurements from the data; i.e. it provides a criterion for successful measurement. When nominal-ordinal data are given numerical values, the researcher can delineate the magnitute of the value as it correlates with the construct of the test. No longer do we have to take nominative-ordinal data and... Read more
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