Main description:

Designed for medical researchers without a background in statistics, this text takes readers easily from basic boxplots and t-tests to linear and logistic regression and survival analysis to more complex generalized linear and nonlinear models and longitudinal data analysis. With many examples and data drawn from real biomedical research, the book focuses on practical statistical analyses using SPSS. It requires no prior statistical background and only assumes familiarity with elementary mathematics. A solutions manual and figures slides are available with qualifying course adoption.

Contents:

THE FOUNDATION: Data Summaries: Tables and Graphs. Probability and Distributions. Statistical Inference for One and Two Groups: Numeric Outcomes. Statistical Inference for One and Two Groups: Binary Outcomes. REGRESSION MODELS: ANOVA. Simple Linear Regression. Multiple Regression. Logistic Regression. Survival Analysis. ADVANCED REGRESSION: Multinomial Regression for Nominal Outcomes. Cumulative Logistic and Probit Models for Ordinal Outcomes. Additional Topics. REPEATED MEASURES AND LONGITUDINAL DATA: Repeated Measures ANOVA. Models for Longitudinal Numeric Outcomes. Mixed-Effect Models for Longitudinal Numeric Data. Models for Longitudinal Binary Outcomes.