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Modelling Frailty for Bivariate Data

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Bivariate Modelling of Epidemiological Data

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Modelling Survival Data in Medical Research

of examples from biomedical research. Well known for its nontechnical style, this third edition contains new chapters on frailty models and their;

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Data Analysis Using Hierarchical Generalized Linear Models with R

within the field and, using data examples, illustrates how to analyse various kinds of data using R. It provides a likelihood approach to;

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Data Analysis Using Hierarchical Generalized Linear Models with R

within the field and, using data examples, illustrates how to analyse various kinds of data using R. It provides a likelihood approach to;

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Frailty Models in Survival Analysis

The concept of frailty offers a convenient way to introduce unobserved heterogeneity and associations into models for survival data. In its;

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Statistical Modelling of Survival Data with Random Effects

This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h;

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Frailty Model

survival data. In this book different methods based on the frailty model are described and it is demonstrated how they can be used to analyze;

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Nonparametric Analysis of Bivariate Censored Data

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Nonparametric Analysis of Bivariate Censored Data

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Applied Univariate, Bivariate, and Multivariate Statistics Using Python - A Beginner's Guide to Advanced Data Analysis

also earn a place in the libraries of researchers and data analysts seeking a quick go-to resource for univariate, bivariate, and multivariate;

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Univariate Bivariate & Multivariate Stat

A practical source for performing essential statistical analyses and data management tasks in R Univariate, Bivariate, and Multivariate;

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Analysis for Time-to-Event Data under Censoring and Truncation

Survival Analysis for Bivariate Truncated Data provides readers with a comprehensive review on the existing works on survival analysis;

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Statistical Modelling in Biostatistics and Bioinformatics

and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling;

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Statistical Modelling in Biostatistics and Bioinformatics

and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling;

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Bivariate Data Analysis

The purpose of this book is to help the users of computerised statistical packages make the correct statistical choices to match the data;

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Advances in Credit Risk Modelling and Corporate Bankruptcy Prediction

accompanied by a careful explanation of model derivation issues. This practical and empirically-based approach makes the book an ideal resource for;

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Advances in Credit Risk Modelling and Corporate Bankruptcy Prediction

accompanied by a careful explanation of model derivation issues. This practical and empirically-based approach makes the book an ideal resource for;

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Living with Frailty

Increasingly, we question 'what makes us healthy?', as well as 'what makes us ill?'. What does this shift mean for frailty? Almost wholly;

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Living with Frailty

Increasingly, we question 'what makes us healthy?', as well as 'what makes us ill?'. What does this shift mean for frailty? Almost wholly;

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Frailty, An Issue of Clinics in Geriatric Medicine

This issue of Clinics in Geriatric Medicine, Guest Edited by James Watson, MD, will feature such article topics as: Frailty and Late Life;

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Frailty and Sarcopenia in Cirrhosis

novel diagnostic methods, while spotlighting treatment and management strategies for frailty and sarcopenia. The book also focuses on special;

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Applied Cross-Cultural Data Analysis for Social Work

Applied Cross-Cultural Data Analysis for Social Work is a research guide for examining and interpreting data for the purpose of cultural;

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Uncertainty Modelling and Quality Control for Spatial Data

Quality Control for Spatial Data introduces methods for managing uncertainties-such as data of questionable quality-in geographic information;

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Uncertainty Modelling and Quality Control for Spatial Data

Quality Control for Spatial Data introduces methods for managing uncertainties-such as data of questionable quality-in geographic information;

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Modelling Binary Data

developments have emerged, accompanied by the steady growth of statistical computing. Mixed models for binary data analysis and procedures that lead to;

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Modelling Binary Data

developments have emerged, accompanied by the steady growth of statistical computing. Mixed models for binary data analysis and procedures that lead to;

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