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Springer - Biased Sampling and Over-identified Parameter Problems

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Description

This academic text from the ICSA Book Series in Statistics provides a deep look into biased sampling problems and over-identified parameter estimation. Known in Econometrics as choice-based sampling, these issues impact various research fields including Medicine, Epidemiology, Public Health, Social Sciences, and Economics. Readers will find comprehensive coverage of essential topics such as causal inference, missing data problems, and meta-analysis. The book also explores specialized areas like case and control studies, renewal processes, length biased sampling, capture and recapture problems, and case cohort studies. It further addresses exponential tilting genetic mixture models, making it a valuable resource for researchers and professionals working with complex statistical data sets.

Key Features

Covers biased sampling problems also known as choice-based sampling in Econometrics.

Addresses over-identified parameter estimation problems for advanced research.

Includes vital topics like causal inference and missing data problems.

Explores applications in Medicine, Epidemiology, Public Health, and Social Sciences.

Provides detailed analysis of case and control studies and meta-analysis.

Discusses specialized subjects like renewal processes and capture and recapture problems.

Product Specifications

Colour
White
Format
hardcover
Domain
Amazon UK
Release Date
29 June 2017
Listed Since
06 April 2017

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No barcode data available

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