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Analysis of Nominal Data

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The updated second edition offers expanded discussions of the chi square test of significance and the potential measures of association available for use with categoric data. Reviewing basic techniques in analysis of nominal data, this paper employs survey research data on party identification and ideologies to indicate which measures and tests are most appropriate for particular theoretical concerns. This book serves as an ideal primer for Volume 20, Log-Linear Models.

Analysis of Covariance

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This book presents a technique for analyzing the effects of variables, groups, and treatments in both experimental and observational settings. Analysis of Covariance considers not only the main effects of one variable upon another, but also (like analysis of variance) the effects of groups of cases.

Canonical Analysis and Factor Comparison

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An advanced study which presumes a knowledge of multiple regression and factor analysis techniques, this paper considers two techniques for comparing entire sets of data, and develops the canonical correlation model as an extension of regression analysis in which there are several dependent variables.

Dynamic Modeling

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Outlines the theory behind, and techniques for, using dynamic modeling, taking the reader through a series of increasingly complex models. At each step, examples are used to claify applications of different equation models.

Causal Modeling

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Retains complete coverage of the first edition, while amplifying key areas such as direct/indirect effects, standardized/unstandardized variables, multicollinie-arity, and nonrecursive modeling.

Exploratory Data Analysis

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An Introduction to the underlying principles, central concepts, and basic techniques for conducting and understanding exploratory data analysis - with numerous social science examples.

Discriminant Analysis

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Discriminant Analysis allows a researcher to study the difference between two or more groups of objects with respect to several variables simultaneously, determining whether meaningful differences exist between the groups and identifying the discriminating power of each variable.

Multiple Indicators

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A presentation and critique of the use of multiple measures of theoretical concepts to assess both validity, using the multirait-multimethod matrix, and reliablity, using multiple indicators with a path analytic framework.

Tests of Significance

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An elementary introduction to significance testing, this paper provides a conceptual and logical basis for understanding these tests.

Interrupted Time Series Analysis

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Describes ARIMA, or Box-Tiao models, widely used in the analysis of interrupted time series quasi-experiments. Assumes no statistical background beyond simple correlation.