Del 140 - Quantitative Applications in the Social Sciences

Confidence Intervals

Häftad, Engelska, 2003

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Smithson first introduces the basis of the confidence interval framework and then provides the criteria for "best" confidence intervals, along with the trade-offs between confidence and precision. Next, using a reader-friendly style with lots of worked out examples from various disciplines, he 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.

Produktinformation

Utgivningsdatum2003-01-14
Mått139 x 215 x 6 mm
Vikt140 g
FormatHäftad
SpråkEngelska
SerieQuantitative Applications in the Social Sciences
Antal sidor104
Upplaga1
FörlagSAGE Publications
ISBN9780761924999

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Sociologi inom Samhalle och politik
Teknik: allmänt inom Naturvetenskap och teknik

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, and Intergroup Aspects (1999). His other publications include more than 170 refereed journal articles and book chapters. His primary research interests are in judgment and decision making under ignorance and uncertainty, statistical methods for the social sciences, and applications of fuzzy set theory to the social sciences.

Ch 1 Introduction and OverviewCh 2 Confidence Statements and Interval EstimatesWhy Confidence Intervals?Ch 3 Central Confidence IntervalsCentral and Standardizable versus Noncentral DistributionsConfidence Intervals Using the Central t and Normal DistributionsConfidence Intervals Using the Central Chi-Square and F DistributionsTransformation PrincipleCh 4 Noncentral Confidence Intervals for Standardized Effect SizesNoncentral DistributionsComputing Noncentral Confidence IntervalsCh 5 Applications in Anova and RegressionFixed-Effects ANOVARandom-Effects ANOVAA Priori and Post-Hoc ContrastsRegression: Multiple, Partial, and Semi-Partial CorrelationsEffect-Size Statistics for MANOVA and Setwise RegressionConfidence Interval for a Regression CoefficientGoodness of Fit Indices in Structural Equations ModelsCh 6 Applications in Categorical Data AnalysisOdds Ratio, Difference between Proportions and Relative RiskChi-Square Confidence Intervals for One VariableTwo-Way Contingency TablesEffects in Log-Linear and Logistic Regression ModelsCh 7 Significance Tests and Power AnalysisSignificance Tests and Model ComparisonPower and PrecisionDesigning Studies Using Power Analysis and Confidence IntervalsConfidence Intervals for PowerConcluding RemarksReferencesAbout the Author