Buch, Englisch, 248 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 4044 g
Analysis of Categorical Data
Buch, Englisch, 248 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 4044 g
ISBN: 978-981-10-9272-5
Verlag: Springer Nature Singapore
The importance of sample surveys today cannot be overstated. From voters’ behaviour to fields such as industry, agriculture, economics, sociology, psychology, investigators generally resort to survey sampling to obtain an assessment of the behaviour of the population they are interested in. Many large-scale sample surveys collect data using complex surveydesigns like multistage stratified cluster designs. The observations using these complex designs are not independently and identically distributed – an assumption on which the classical procedures of inference are based. This means that if classical tests are used for the analysis of such data, the inferences obtained will be inconsistent and often invalid. For this reason, many modified test procedures have been developed for this purpose over the last few decades.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsstatistik, Demographie
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Epidemiologie, Medizinische Statistik
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
Weitere Infos & Material
Chapter 1. Preliminaries.- Chapter 2. The Design-Effects and Mis-Speci?cation Effects.- Chapter 3. Some Classical Models in Categorical Data Analysis.- Chapter 4. Analysis of Categorical Data under a Full Model.- Chapter 5. Analysis of Categorical Data under Log-Linear Models.- Chapter 6. Analysis of Categorical Data under Logistic Regression Model.- Chapter 7. Analysis in the Presence of Classi?cation Errors.- Chapter 8. Approximate MLE’s from Survey Data.