La legittimazione a ricorrere nel processo amministrativo / Silvia Mirate

• Record Nr.: UNICAMPANIASUN0122859
• Autore: Mirate, Silvia
• Pubbl/distr/stampa: Milano : Angeli, 2018
• ISBN: 8-88-917-8094-2
• Descrizione fisica: 408 p. ; 23 cm.
• Soggetti: Ricorsi amministrativi - Italia
• Lingua di pubblicazione: Italiano
• Formato: Materiale a stampa
• Livello bibliografico: Monografia

Margins of error [[electronic resource] ] : a study of reliability in survey measurement / / Duane F. Alwin

• Record Nr.: UNINA9910830436103321
• Autore: Alwin Duane F (Duane Francis), <1944->
• Pubbl/distr/stampa: Hoboken, N.J., : Wiley-Interscience, c2007
• ISBN: 1-280-93516-2; 9786610935161; 0-470-14631-1; 0-470-14630-3
• Descrizione fisica: 1 online resource (410 p.)
• Collana: Wiley series in survey methodology
• Disciplina: 001.4/33; 001.433; 519.52
• Soggetti: Surveys; Error analysis (Mathematics)
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. 367-382) and index.
• Nota di contenuto: Margins of Error: A Study of Reliability in Survey Measurement; Contents; Preface; Acknowledgments; Foreword; 1. Measurement Errors in Surveys; 1.1 Why Study Survey Measurement Error?; 1.2 Survey Errors; 1.3 Survey Measurement Errors; 1.4 Standards of Measurement; 1.5 Reliability of Measurement; 1.6 The Need for Further Research; 1.7 The Plan of this Book; 2. Sources of Survey Measurement Error; 2.1 The Ubiquity of Measurement Errors; 2.2 Sources of Measurement Error in Survey Reports; 2.3 Consequences of Measurement Error; 3. Reliability Theory for Survey Measures; 3.1 Key Notation; 3.2 Basic Concepts of Classical Reliability Theory3.3 Nonrandom Measurement Error; 3.4 The Common-Factor Model Representation of CTST; 3.5 Scaling of Variables; 3.6 Designs for Reliability Estimation; 3.7 Validity and Measurement Error; 3.8 Reliability Models for Composite Scores; 3.9 Dealing with Nonrandom or Systematic Error; 3.10 Sampling Considerations; 3.11 Conclusions; 4. Reliability Methods for Multiple Measures; 4.1 Multiple Measures versus Multiple Indicators; 4.2 Multitrait-Multimethod Approaches; 4.3 Common-Factor Models of the MTMM Design; 4.4 Classical True-Score Representation of the MTMM Model4.5 The Growing Body of MTMM Studies; 4.6 An Example; 4.7 Critique of the MTMM Approach; 4.8 Where Are We?; 5. Longitudinal Methods for Reliability Estimation; 5.1 The Test-Retest Method; 5.2 Solutions to the Problem; 5.3 Estimating Reliability Using the Quasi-Markov Simplex Model; 5.4 Contributions of the Longitudinal Approach; 5.5 Components of the Survey Response; 5.6 Where to from Here?; 6. Using Longitudinal Data to Estimate Reliability Parameters; 6.1 Rationale for the Present Study; 6.2 Samples and Data; 6.3 Domains of Measurement6.4 Statistical Estimation Strategies; 6.5 Comparison of Methods of Reliability Estimation; 6.6 The Problem of Attrition; 6.7 Which Reliability Estimates?; 6.8 Conclusions; 7. The Source and Content of Survey Questions; 7.1 Source of Information; 7.2 Proxy Reports; 7.3 Content of Questions; 7.4 Summary and Conclusions; 8. Survey Question Context; 8.1 The Architecture of Survey Questionnaires; 8.2 Questions in Series versus Questions in Batteries; 8.3 Location in the Questionnaire; 8.4 Unit Length and Position in Series and Batteries; 8.5 Length of Introductions to Series and Batteries8.6 Conclusions; 9. Formal Properties of Survey Questions; 9.1 Question Form; 9.2 Types of Closed-Form Questions; 9.3 Number of Response Categories; 9.4 Unipolar versus Bipolar Scales; 9.5 Don't Know Options; 9.6 Verbal Labeling of Response Categories; 9.7 Survey Question Length; 9.8 Conclusions; 10. Attributes of Respondents; 10.1 Reliability as a Population Parameter; 10.2 Respondent Attributes and Measurement Error; 10.3 Age and Reliability of Measurement; 10.4 Schooling and Reliability of Measurement; 10.5 Controlling for Schooling Differences
• Sommario/riassunto: Enhance the quality of survey results by recognizing and reducing measurement errors. Margins of Error: A Study of Reliability in Survey Measurement demonstrates how and hwy identifying the presence and extent of measurement errors in survey data is essential for improving the overall collection and analysis of the data. The author outlines the consequences of ignoring survey measurement errors and also discusses ways to detect and estimate the impact of these errors. This book also provides recommendations of improving the quality of survey data. Logically organized and clearly wri