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Applied Mathematics for the Analysis of Biomedical Data: Models, Methods, and MATLAB

Features a practical approach to the analysis of biomedical data via mathematical methods and provides a MATLAB(R) toolbox for the;

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Biostatistics for Epidemiologists

Biostatistics for Epidemiologists is a unique book that provides a collection of methods that can be used to analyze data in most;

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Handbook of Neuroimaging Data Analysis

This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development;

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Handbook of Neuroimaging Data Analysis

This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development;

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A Biostatistics Toolbox for Data Analysis

involved in the analysis of data. It makes the link from statistical theory to data analysis, focusing on the methods and data types most common;

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Biostatistics for Human Genetic Epidemiology

data analysis. It examines probabilistic and statistical theories for modeling human genetic epidemiology - leading the readers;

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Statistics in MATLAB

analysis. Statistics in MATLAB: A Primer is an ideal reference for undergraduate and graduate students in engineering, mathematics, statistics;

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Statistics in MATLAB

analysis Statistics in MATLAB: A Primer is an ideal reference for undergraduate and graduate students in engineering, mathematics, statistics;

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Statistical Modeling in Biomedical Research

and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their;

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Biostatistics and Computer-based Analysis of Health Data Using SAS

This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of SAS for data;

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Applied Biostatistics for the Health Sciences, Sec ond Edition

studies, and data set examples A comprehensive exploration of population descriptions, including qualitative and quantitative variables;

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Modern Statistical Methods for Health Research

interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data;

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Statistical Modeling in Biomedical Research: Contemporary Topics and Voices in the Field

and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their applications;

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Biostatistics and Computer-based Analysis of Health Data using Stata

This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of Stata for data;

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Applied Missing Data Analysis in the Health Sciences

This book provides a modern, hands-on guide to the essential concepts and ideas for analyzing data with missing observations in the field;

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Computational Intelligence Methods for Bioinformatics and Biostatistics

medicine, and data integration and analysis in omic-science.;

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Biostatistics in Public Health Using STATA

of statistics in public health, it facilitates a clear understanding of the basic commands of STATA for reading and saving databases. The book;

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Introductory Biostatistics 2nd Edition

. Subsequently, the book focuses on more advanced topics with coverage of regression analysis, logistic regression, methods for count data, analysis;

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Practical Guides to Biostatistics and Epidemiology

This practical guide to survival data and its analysis for readers with a minimal background in statistics shows why the analytic methods;

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Applied Categorical and Count Data Analysis

that include models for zero-modified count outcomes, parametric and semiparametric longitudinal data analysis, reliability analysis, and;

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Analysis of Correlated Data with SAS and R

for the analysis of hierarchical binary, count and continuous response data. It explains how to use procedures in SAS and packages in R for;

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Analysis of Correlated Data with SAS and R

for the analysis of hierarchical binary, count and continuous response data. It explains how to use procedures in SAS and packages in R for;

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Biostatistics

Regression, Analysis of Survey Data, and Study Designs. The book is recommended for students in the health sciences, public health;

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Biostatistics for Epidemiology and Public Health Using R

analysis and graphical output. This is the first textbook to present classical biostatistical analysis for epidemiology and related public health;

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Understanding Biplots

to be a useful and reliable method for the visualization of multidimensional data associated with, for example, principal component analysis;

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Using R for Biostatistics

use of data. Beginning with a focus on data from a parametric perspective, the authors address topics such as Student t-Tests for independent;

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Using R for Biostatistics

use of data. Beginning with a focus on data from a parametric perspective, the authors address topics such as Student t-Tests for independent;

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