Statistical methods in discrimination litigation. (2014)

• Record Type: Book
• Further Information: Note: Edited by D.H. Kaye, Mikel Aickin.
• Editors: Kaye, D. H (David H.), 1947-; Aickin, Mikel
• Contents: Cover; Half Title; Title Page; Copyright Page; Contents; Preface; Contributors; 1. The Place of Statistics in Establishing Unconstitutional Acts of Discrimination; 1.1. INTRODUCTION; 1.2. EQUAL PROTECTION IN A NUTSHELL; 1.3. DISCRIMINATION IN AD HOC DECISIONMAKING; 1.4. DISCRIMINATION IN THE APPLICATION OF A RULE; 1.4.1. Discriminatory Prosecutions; 1.4.2. Racial Discrimination in Capital Sentencing; 1.4.3. Discrimination in Jury Selection; 1.5. DISCRIMINATION IN THE FORMULATION OF A RULE; 1.6. DISCRIMINATION IN THE OPERATION OF A RULE; ACKNOWLEDGMENTS; REFERENCES 2. Statistical Evidence of Discrimination in Jury Selection2.1. INTRODUCTION; 2.2. STATISTICAL ANALYSIS OF OVERALL REPRESENTATION RATES; 2.2.1. The Measure of Underrepresentation; 2.2.2. The Relevant Population; 2.2.3. How Much Is Too Much? The Role of Formal Statistical Inference; 2.3. STATISTICAL ANALYSIS OF PECULIARITIES; ACKNOWLEDGMENTS; NOTES; REFERENCES; 3. Claims of Employment Discrimination Under Title VII of the Civil Rights Act of 1964; 3.1. A SKETCH OF TITLE VII; 3.2. CLAIMS OF DISPARATE TREATMENT; 3.2.1. Individual Claims; 3.2.2. Class Claims; 3.3. CLAIMS OF DISPARATE IMPACT 3.3.1. Griggs v. Duke Power Co.3.3.2. Proof of Adverse Impact; 3.3.3. Business Justification; 3.3.4. Claims of Disparate Impact and Affirmative Action; 3.4. CONCLUSION; ACKNOWLEDGMENT; REFERENCES; 4. Defining the Relevant Population in Employment Discrimination Cases; 4.1. INTRODUCTION; 4.2. APPLICANT FLOW; 4.3. THE LABOR MARKET AND THE EMPLOYER'S WORK FORCE; 4.4. PROJECTING THE EMPLOYER'S REQUIREMENTS ON THE LABOR FORCE; 4.5. AN EXAMPLE; 4.6. CONCLUSION; NOTES; REFERENCE; 5. Regression Analysis in Discrimination Cases; 5.1. INTRODUCTION; 5.1.1. Purpose and Use of a Statistical Analysis 5.1.2. Model Building5.2. REGRESSION AS DATA ANALYSIS; 5.3. REGRESSION AS A PROBABILISTIC MODEL; 5.4. REGRESSION AS AN APPROXIMATION; 5.4.1. Choice and Quantification of the Variables; 5.4.2. Building the Regression; 5.4.3. Consequences of Using an Inadequate Equation; 5.4.4. Missing Variables; 5.5. CONCLUSIONS; REFERENCES; 6. The Perverse Logic of Reverse Regression; 6.1. INTRODUCTION; 6.2. PROBABILISTIC RELATIONS AND THE STRATEGY OF REGRESSION; 6.3. INVESTIGATING DISCRIMINATION WITH DIRECT AND REVERSE REGRESSION; 6.3.1. The Problem of Bias in Regression; 6.3.2. Two Examples 6.3.3. General Modelling in the 2 X 2 Case6.4. PERCEPTIONS OF DISCRIMINATION; 6.5. CONCLUSIONS; NOTES; REFERENCES; 7. Measurement Error and Regression Analysis in Employment Cases; 7.1. INTRODUCTION; 7.2. A MECHANISM FOR MEASUREMENT ERROR BIAS; 7.3. AN EXAMPLE OF MEASUREMENT ERROR BIAS IN A REGRESSION MODEL; 7.4. MEASUREMENT ERROR BIAS IN A MORE GENERAL MODEL; 7.5. FIRST SPECIAL CASE: PRODUCTIVITY AND GENDER CAUSE THE u·PROXIES; 7.6. SECOND SPECIAL CASE: GENDER AND u·PROXIES CAUSE PRODUCTIVITY; 7.7. ALTERNATIVE ANALYSES; 7.8. CONCLUSION; ACKNOWLEDGMENT; NOTES; REFERENCES
• Publisher Details: Boca Raton, FL : CRC Press
• Publication Date: 2014
• Extent: 1 online resource
• Subjects: 344.7301133; Psychology -- Methodology; Psychology -- Statistics; Psychology; Psychology -- Methodology; Electronic books; Statistics
• Languages: English
• ISBNs: 9781498710480; 1498710484
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.