Survey Data Analysis in Applied Settings provides readers with an accessible hands-on approach to modern day applied survey data analysis. It offers detailed insights and step-by-step methods and techniques to collect, prepare, analyze and interpret survey data. The book covers the presentation of data, an overview of survey design, nonresponse and missing data analysis, and an awareness of the hidden biases that often underlie poorly analyzed survey data. A companion website features computer code (primarily for R) that can be manipulated by the reader for their own purpose.
Survey Data Analysis in Applied Settings provides readers with an accessible hands-on approach to modern day applied survey data analysis. It offers detailed insights and step-by-step methods and techniques to collect, prepare, analyze and interpret survey data. The book covers the presentation of data, an overview of survey design, nonresponse and missing data analysis, and an awareness of the hidden biases that often underlie poorly analyzed survey data. A companion website features computer code (primarily for R) that can be manipulated by the reader for their own purpose.
Research Assistant Professor, Northwestern University. Dr. Griffith¿s MD, MRCP, FRCR area of expertise is applying measurement science and psychometrics to clinical problems. He has extensive experience both researching and teaching in this area. He¿s additionally provided consultation on the topic to a variety of non-profits, pharmaceutical, and medical device companies. He maintains a clinical practice in Chicago focused on cognitive behavioral therapy for adults with anxiety and depression. He has published over 70 papers on various aspects of psychometrics and psychological assessment.
Inhaltsangabe
1. Survey Design 2. Gathering Data 3. Preparing Data for Analysis 4. Scoring Questionnaires 5. Exploring the Data 6. Basic Survey and Psychometric Analysis 7. Data Presentation, Graphing and Summarizing Results 8. Advanced Survey Analysis
1. Survey Design 2. Gathering Data 3. Preparing Data for Analysis 4. Scoring Questionnaires 5. Exploring the Data 6. Basic Survey and Psychometric Analysis 7. Data Presentation, Graphing and Summarizing Results 8. Advanced Survey Analysis
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