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Springer Emerging Topics in Modeling Interval-Censored Data

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Description

This academic text from Springer focuses on advanced statistical methods for modeling interval-censored survival data. Often found in biomedical and public health research, this specific type of data is frequently misidentified as right-censored data, which can lead to incorrect statistical inferences. This book addresses those complexities to improve the accuracy of research and training. By bringing together a group of internationally leading researchers, the book explores the historical development and modern advancements in the field. It is designed to boost research and education by providing systematic discussions on statistical modeling techniques. This resource is essential for professionals and students looking to advance their understanding of complex survival data analysis.

Key Features

This Springer publication provides a systematic discussion on the historical development of statistical modeling.

The text addresses the complexities of interval-censored survival data to prevent erroneous statistical inference.

It serves as a resource to boost research, education, and training in the field of statistics.

The content explores methods specifically for data commonly collected in public health and biomedical research.

Internationally leading researchers contribute to the discussion of emerging topics in statistical methods.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
30 November 2022
Listed Since
22 June 2022

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