£120.10

Springer Unified Methods for Censored Longitudinal Data and Causality

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Description

This Springer Series in Statistics volume addresses advanced statistical methods for analysing complex observational studies and clinical trials involving time-dependent data collection across medicine, biology, epidemiology, sociology, and economics. The book provides comprehensive coverage of estimation techniques for finite dimensional parameters within population distributions, with particular focus on handling censored longitudinal data and causal inference. Designed for researchers, statisticians, and practitioners working with large-scale datasets collected over extended periods, this resource bridges the gap between classical survival analysis and modern causal inference methods. The text draws on decades of computational and technological advancement to present unified approaches that consolidate fragmented methodologies into coherent frameworks for addressing real-world research challenges in clinical and observational settings.

Key Features

Covers unified statistical methods specifically designed for censored longitudinal data analysis across multiple scientific disciplines.

Addresses causal inference and parameter estimation problems arising from time-dependent observational processes in clinical research.

Published by Springer as part of their established Statistics series, providing authoritative peer-reviewed content for advanced study.

Applicable to complex studies in medicine, biology, epidemiology, sociology, and economics involving large-scale subject data collection.

Bridges computation and information technology developments with practical estimation strategies for modern research applications.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
14 January 2003
Listed Since
22 December 2006

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No barcode data available

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