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Statistical modelling in biostatistics and bioinformatics : selected papers / [edited by] Gilbert MacKenzie and Defen Peng.

Contributor(s): Material type: TextTextSeries: Contributions to statisticsPublication details: Switzerland : Springer, 2014.Description: xiv, 244 p. illISBN:
  • 9783319045788 (hard cover : alk. paper)
Subject(s): DDC classification:
  • 23 M156 000SB:570
Contents:
Introduction -- Part I. Survival Modelling Multivariate Interval-Censored Survival Data: Parametric, Semi-Parametric and Non-Parametric Models; MacKenzie and Ha -- Multivariate Survival Models Based on the GTDL; Lynch and MacKenzie -- Frailty Models with Structural Dispersion; Martinez and Hinde -- Random Effects Ordinal Time Models for Grouped Toxicological Data from a Biological Control Assay -- Part II. Longitudinal Modelling & Time Series Modelling Seasonality and Structural Breaks: Visitors to NZ and 9/11; Allais and Bosco -- Forecasting the Insolvency Risk of the Customers of an Automotive Financial Service; Xu and MacKenzie -- On Joint Modelling of Constrained Mean and Covariance Structures in Longitudinal Data -- Part III. Statistical Model Development Hierarchical Generalized Nonlinear Models; Durio and Isaia -- Comparing Robust Regression Estimators to Detect Data Clusters: A Case Study; Coffey, Hinde and Garcia -- Finite Mixture Model Clustering of SNP Data; Peng and MacKenzie -- Discrepancy and Choice of Reference Subclass in Categorical Regression Models -- Part IV. Applied Statistical Modelling Statistical Methods for Detecting Selective Sweeps; Brophy, Gibson, Wayne and Connolly -- A Mixture Model and Bootstrap Analysis to Assess Reproductive Allocation in Plants; Conde and MacKenzie -- On Model Selection Algorithms in Multi-Dimensional Contingency Tables -- Postscript: Durio and MacKenzie -- Obituary: Professor Ennio Isaia.
Summary: This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion.
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Introduction --
Part I. Survival Modelling
Multivariate Interval-Censored Survival Data: Parametric, Semi-Parametric and Non-Parametric Models; MacKenzie and Ha --
Multivariate Survival Models Based on the GTDL; Lynch and MacKenzie --
Frailty Models with Structural Dispersion; Martinez and Hinde --
Random Effects Ordinal Time Models for Grouped Toxicological Data from a Biological Control Assay --

Part II. Longitudinal Modelling & Time Series
Modelling Seasonality and Structural Breaks: Visitors to NZ and 9/11; Allais and Bosco --
Forecasting the Insolvency Risk of the Customers of an Automotive Financial Service; Xu and MacKenzie --
On Joint Modelling of Constrained Mean and Covariance Structures in Longitudinal Data --

Part III. Statistical Model Development
Hierarchical Generalized Nonlinear Models; Durio and Isaia --
Comparing Robust Regression Estimators to Detect Data Clusters: A Case Study; Coffey, Hinde and Garcia --
Finite Mixture Model Clustering of SNP Data; Peng and MacKenzie --
Discrepancy and Choice of Reference Subclass in Categorical Regression Models --

Part IV. Applied Statistical Modelling
Statistical Methods for Detecting Selective Sweeps; Brophy, Gibson, Wayne and Connolly --
A Mixture Model and Bootstrap Analysis to Assess Reproductive Allocation in Plants; Conde and MacKenzie --
On Model Selection Algorithms in Multi-Dimensional Contingency Tables --
Postscript: Durio and MacKenzie --
Obituary: Professor Ennio Isaia.

This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion.

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