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Tutorials in Biostatistics Statistical Modelling of Complex Medical Data 1st Edition by Ralph BD Agostino ISBN 0470023708 9780470023709

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Tutorials in Biostatistics Statistical Modelling of Complex Medical Data Volume 2 Ralph B. D’Agostino Digital Instant Download

Author(s): Ralph B. D’Agostino
ISBN(s): 9780470023709, 0470023708
Edition: Volume 2
File Details: PDF, 15.81 MB
Year: 2004
Language: english
SKU: EB-2330992 Category: Tag:

Tutorials in Biostatistics Statistical Modelling of Complex Medical Data 1st Edition by Ralph BD Agostino – Ebook PDF Instant Download/Delivery: 0470023708, 9780470023709
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ISBN 10: 0470023708 
ISBN 13: 9780470023709
Author: Ralph BD Agostino

The Tutorials in Biostatistics have become a very popular feature of the prestigious Wiley journal, Statistics in Medicine (SIM). The introductory style and practical focus make them accessible to a wide audience including medical practitioners with limited statistical knowledge.   This book represents the second of two volumes presenting the best tutorials published in SIM, focusing on statistical modeling of complex data. Topics include clustered data, hierarchical models, mixed models, genetic modeling, and meta-analysis. Each tutorial is focused on a medical problem, has been fully peer-reviewed and edited, and is authored by leading researchers in biostatistics.   Many articles include an appendix on the latest developments since publication in the journal and additional references. This will appeal to statisticians working in medical research, as well as statistically-minded clinicians, biologists, epidemiologists and geneticists. It will also appeal to graduate students of biostatistics. 

Tutorials in Biostatistics Statistical Modelling of Complex Medical Data 1st Table of contents:

  • Chapter 1: Fundamentals of Statistical Modelling

    • Introduction to Statistical Models

    • Overview of Common Statistical Techniques in Biostatistics

    • Variables and Data Types in Medical Research

    • Model Assumptions and Diagnostics

  • Chapter 2: Data Types and Sources in Medical Research

    • Types of Medical Data: Cross-Sectional, Longitudinal, and Survival Data

    • Data Collection Methods in Medical Research

    • Dealing with Missing Data

    • Data Preprocessing and Transformation

  • Chapter 3: Regression Models for Medical Data

    • Simple and Multiple Linear Regression

    • Generalized Linear Models (GLMs)

    • Model Selection and Interpretation of Coefficients

    • Handling Nonlinear Relationships in Medical Data

  • Chapter 4: Survival Analysis in Medical Research

    • Introduction to Survival Data and Censoring

    • Kaplan-Meier Estimation and Log-Rank Test

    • Cox Proportional Hazards Model

    • Competing Risks and Multivariate Survival Models

  • Chapter 5: Multilevel and Hierarchical Models

    • Introduction to Multilevel Data Structures

    • Mixed-Effects Models: Random Intercepts and Slopes

    • Model Interpretation in Hierarchical Data

    • Applications in Clinical Trials and Longitudinal Studies

  • Chapter 6: Time Series and Longitudinal Data Analysis

    • Overview of Time Series Data in Medicine

    • Longitudinal Data Analysis Techniques

    • Autoregressive Models and Their Applications

    • Generalized Estimating Equations (GEE)

  • Chapter 7: Generalized Linear Models (GLMs) and Extensions

    • GLM Framework and Link Functions

    • Poisson and Negative Binomial Models for Count Data

    • Logistic Regression for Binary Outcomes

    • Model Assessment and Goodness-of-Fit

  • Chapter 8: Multivariate Analysis in Medical Data

    • Principal Component Analysis (PCA)

    • Factor Analysis and Cluster Analysis

    • Canonical Correlation and Multivariate Regression

    • Applications in Medical Imaging and Genetic Data

  • Chapter 9: Bayesian Statistical Modelling

    • Introduction to Bayesian Inference

    • Priors, Likelihood, and Posterior Distributions

    • Bayesian Models in Medical Data

    • Markov Chain Monte Carlo (MCMC) and Model Estimation

  • Chapter 10: Machine Learning in Medical Statistics

    • Overview of Machine Learning Techniques in Biostatistics

    • Supervised Learning: Classification and Regression

    • Unsupervised Learning: Clustering and Dimensionality Reduction

    • Model Validation and Evaluation

  • Chapter 11: Advanced Statistical Techniques for Complex Medical Data

    • Nonparametric Methods for Complex Data

    • Latent Variable Models and Structural Equation Modeling (SEM)

    • Propensity Score Matching and Causal Inference

    • High-Dimensional Data and Regularization Methods

  • Chapter 12: Statistical Software for Medical Data Analysis

    • Introduction to Statistical Software: R, SAS, SPSS

    • Using R for Statistical Modelling and Data Analysis

    • Visualizing Medical Data: Plots and Graphs

    • Automating Analyses with Scripts

  • Chapter 13: Applications in Clinical Trials and Epidemiology

    • Statistical Modelling in Randomized Controlled Trials (RCTs)

    • Epidemiological Studies: Cohort and Case-Control

    • Adjusting for Confounding and Bias in Medical Studies

    • Meta-Analysis and Systematic Reviews

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Tags: Ralph BD Agostino, Tutorials, Biostatistics Statistical, Medical Data