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Confidence Intervals

Confidence Intervals

November 2002 | 104 pages | SAGE Publications, Inc
Using lots of easy to understand examples from different disciplines, the author introduces the basis of the confidence interval framework and provides the criteria for `best' confidence intervals, along with the trade-offs between confidence and precision.

The book covers such pertinent topics as: the transformation principle whereby a confidence interval for a parameter may be used to construct an interval for any monotonic transformation of that parameter; confidence intervals on distributions whose shape changes with the value of the parameter being estimated; and, the relationship between confidence interval and significance testing frameworks, particularly regarding power.

Ch 1 Introduction and Overview
Ch 2 Confidence Statements and Interval Estimates
Why Confidence Intervals?

Ch 3 Central Confidence Intervals
Central and Standardizable versus Noncentral Distributions

Confidence Intervals Using the Central t and Normal Distributions

Confidence Intervals Using the Central Chi-Square and F Distributions

Transformation Principle

Ch 4 Noncentral Confidence Intervals for Standardized Effect Sizes
Noncentral Distributions

Computing Noncentral Confidence Intervals

Ch 5 Applications in Anova and Regression
Fixed-Effects ANOVA

Random-Effects ANOVA

A Priori and Post-Hoc Contrasts

Regression: Multiple, Partial, and Semi-Partial Correlations

Effect-Size Statistics for MANOVA and Setwise Regression

Confidence Interval for a Regression Coefficient

Goodness of Fit Indices in Structural Equations Models

Ch 6 Applications in Categorical Data Analysis
Odds Ratio, Difference between Proportions and Relative Risk

Chi-Square Confidence Intervals for One Variable

Two-Way Contingency Tables

Effects in Log-Linear and Logistic Regression Models

Ch 7 Significance Tests and Power Analysis
Significance Tests and Model Comparison

Power and Precision

Designing Studies Using Power Analysis and Confidence Intervals

Confidence Intervals for Power

Concluding Remarks
About the Author

Michael Smithson

Michael Smithson is a Professor in the Research School of Psychology at The Australian National University in Canberra, and received his PhD from the University of Oregon. He is the author of Confidence Intervals (2003), Statistics with Confidence (2000), Ignorance and Uncertainty (1989), and Fuzzy Set Analysis for the Behavioral and Social Sciences (1987), co-author of Fuzzy Set Theory: Applications in the Social Sciences (2006) and Generalized Linear Models for Categorical and Limited Dependent Variables (2014), and co-editor of Uncertainty and Risk: Multidisciplinary Perspectives (2008) and Resolving Social Dilemmas: Dynamic, Structural... More About Author

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ISBN: 9780761924999

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