Survey data collection and integration
著者
書誌事項
Survey data collection and integration
Springer, c2013
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内容説明・目次
内容説明
Statistical surveys represent an important source of scientific knowledge and a valid decision support tool in many fields, from social studies to economics, market research, health studies, and others. Scientists have tackled most of the methodological issues concerning surveys and the scientific literature offers excellent proposals for planning and conducting surveys. Nevertheless, surveys often require the achievement of aims that either deviate from the methodology or do not have a specific solution at all.
This book focuses on survey theory and applications, providing insight and innovative solutions to face problems in data collection and integration, complex sample design, opinion questionnaire design, and statistical estimation.
Formal rigour and simple language, together with real-life examples, will make the book suitable to both practitioners involved in applied research and to academics interested in scientific developments in the survey field.
目次
Part 1: Introduction to Statistical Surveys: Critical Points, Challenges and Need for Development (Luigi Biggeri).- Part 2: Questionnaire Design: Measurement Scales for Scoring or Ranking Sets of Interrelated Items (Luigi Fabbris).- Assessing Multi-Item Scales for Subjective Measurement (Cristina Davino and Rosaria Romano).- Statistical Tools in the Joint Analysis of Closed and Open-Ended Questions (Simona Balbi and Nicole Triunfo).- The Use of Self-Anchoring Scales in Social Research: The Cantril Scale for the Evaluation of Community Action Orientation (Immacolata Di Napoli and Caterina Arcidiacono).- Part 3: Sampling Design and Error Estimation: Small Area Estimation of Poverty Indicators ( Monica Pratesi, Caterina Giusti and Stefano Marchetti).- Non-Sampling Errors in Household Surveys: The Bank of Italy's Experience (Giovanni D'Alessio and Giuseppe Ilardi).- Part 4: Data Integration: Enriching a Large Scale Survey from a Representative Sample by Data Fusion: Models and Validation (Tomas Aluja-Banet, Josep Daunis-i-Estadella and Yan Hong Chen).- A Business Survey on Job Vacancies: Integration with Other Sources and Calibration (Diego Bellisai, Stefania Fivizzani and Marina Sorrentino).
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