Download e-book for kindle: Analysis of nominal data, Issue 7 by Henry T. Reynolds

By Henry T. Reynolds

ISBN-10: 0803906536

ISBN-13: 9780803906532

The up to date moment version deals accelerated discussions of the chi sq. attempt of importance and the aptitude measures of organization on hand to be used with categoric facts. Reviewing uncomplicated ideas in research of nominal information, this paper employs survey study facts on occasion identity and ideologies to point which measures and assessments are fabulous for specific theoretical issues. This booklet serves as a fantastic primer for quantity 20, Log-Linear versions.

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Extra resources for Analysis of nominal data, Issue 7

Sample text

The calculation and interpretation of asymmetric measures depend on which variable is considered dependent. There are thus two versionsone when X is considered independent, the other when it is considered dependentand the versions do not normally equal each other. With a symmetric index, by contrast, either variable can be considered dependent. The Interpretation of Measures of Association Since a measure of associationa single numbersupposedly summarizes the information in a table, it should have a clear interpretation.

The only constraints are the two rules described by Iversen. For further information and examples, the reader should consult Reynolds (1977a), Iversen (1979), and Goodman (1969). 3. Measures of Association Introduction Since the usual goodness-of-fit chi square test says only whether two variables may or may not be statistically independent, and by itself it does not give the strength or form of the relationship, one usually calculates a measure of association as the next step in the analysis. A measure of association is a numerical index summarizing the strength or degree of relationship in a two-dimensional cross-classification.

These tables illustrate a well-known principle: If all the frequencies in a cross-classification are multiplied by a constant, K, the magnitude of chi square increases K times. Therefore, in order to interpret meaningfully chi square. we have to look at more than its numerical value. Assessing the "practical" or "theoretical" significnce of a chi square requires that we measure the strength of the relationship. 005NOTE: Table entries are frequencies. Page 22 The conventional chi square test presents another problem of interpretation.

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Analysis of nominal data, Issue 7 by Henry T. Reynolds

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