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£128.26
Springer Biased Sampling and Over-Identified Parameters - Springer Statistics
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Description
Key Features
Addresses biased sampling and choice-based sampling problems across medicine, epidemiology, public health, social sciences and economics.
Covers case and control studies with methodologies for managing sampling bias in clinical research design.
Explores causal inference and missing data problems with statistical techniques for handling incomplete information.
Includes meta-analysis approaches and renewal process methods for complex data synthesis.
Provides solutions for length biased sampling, capture and recapture problems, and case cohort studies.
Features exponential tilting and genetic mixture models for advanced parameter estimation challenges.
Product Specifications
- Brand
- Springer
- Format
- paperback
- ASIN
- 9811352496
- Domain
- Amazon UK
- Release Date
- 09 December 2018
- Listed Since
- 10 December 2018
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