Statistical Methods for Health Sciences

This book offers recently developed statistical methods used in the health sciences. These methods are presented in a comprehensive and systematic manner and include methods to account for what is widely known as intracluster correlation.

COMPARING GROUP MEANS WHEN THE STANDARD ASSUMPTIONS ARE VIOLATED
Introduction
Non-Normality
Heterogeneity of Variances
Non-Independence
STATISTICAL ANALYSIS OF MEASUREMENTS RELIABILITY: THE CASE OF INTERVAL SCALE MEASUREMENTS
Introduction
Models for Reliability Studies
Case 1: The One-Way Random Effects Model
Case 2: The Two-Way Random Effects Model
Case 3: The Two-Way Mixed Effects Model
Covariate Adjustment in the One-Way Random Effects Model
Comparison of Measurement Methods
Comparing the Reliability of Two Methods
Comparing the Precisions of Two Methods
Concordance Correlation as a Measure of Reproducibility
STATISTICAL ANALYSIS OF CROSS-CLASSIFIED DATA
Introduction
Measures of Association in 2x2 Tables
Cross Sectional Sampling (Historical Cohort Studies)
Cohort and Case-Control Studies
Statistical Inference on Odds Ratio
Significance Tests
Interval Estimation
Analysis of Several 2x2 Contingency Tables
Statistical Methods for Bias Reduction
Analysis of Matched Pairs (One Case and One Control)
Estimating the Odds Ratio
Testing the Equality of Marginal Distributions
Statistical Analysis of Clustered Binary Data
Testing Homogeneity
Inference on the Common Odds Ratio
Measure of Interclinician Agreement for Categorical Data
Agreement in 2x2 Tables (Two Clinicians and Two Categories)
Confidence Interval on Kappa in 2x2 Table
Agreement between Two Raters with Multiple Categories
More than Two Clinicians
Assessment of Bias
Statistical Analysis of Medical Screening Tests
Introduction
Estimating Prevalence
Estimating Predictive Value Positive and Predictive Value Negative
Estimation in Double Sampling
Dependent Screening Tests (Multiple Readings)
Estimation of Parameters
Special Topics
Group Testing
Evaluating the Performance of Medical Screening Tests in the Absence of a Gold Standard (Latent Class Models)
LOGISTIC REGRESSION
Introduction
The Logistic Transformation
Coding Categorical Explanatory Variables and Interpretation of Coefficients
Interaction and Confounding
The Goodness of Fit and Model Comparisons
Pearson's X2 - Statistic
The Likelihood Ratio Criterion (Deviance)
Logistic Regression of Clustered Binary Data
Introduction
Intracluster Effects
Analysis of Overdispersed Binomial Data
Full Likelihood Models
Estimating Equations Approach
Logistic Regression for Case-Control Studies
Cohort versus Case-Control Models
Matched Analysis
Conditional Likelihood
Fitting Matched Case-Control Study Data in SAS
THE ANALYSIS OF TIME SERIES
Introduction
Simple Descriptive Methods
Fundamental Concepts in the Analysis of Time Series
Stochastic Process
Stationary Series
The Autocovariance and Autocorrelation Functions
Models for Stationary Time Series
Autoregressive Processes
Moving Average Processes
The Mixed Autoregressive Moving Average Process
Models for Nonstationary Time Series
Nonstationarity in the Mean
Differencing
Arima Models
Nonstationarity in the Variance
Model Specification and Parameter Estimation
Specification
Estimation
Forecasting
The One-Way and Two-Way Analysis of Variance with Time-Series Data
Introduction
One-Way Anova with Correlated Errors
Two-Way Anova with Correlated Errors
REPEATED MEASURES ANALYSIS
Introduction
Examples
Effect of Mycobacterium Inoculation on Weight
Variation in Teenage Pregnancy Rates (TAPR) in Canada
Methods for the Analysis of Repeated Measures Experiments
Basic Models
Hypothesis Testing
Recommended Analysis for Example A
Recommended Analysis for Example B
Missing Observations
The Generalized Estimating Equations Approach