Biostatistics Manual for Health Research

1. Introduction to Biostatistics
Background
What is Biostatistics?
Role of Biostatistics
Aim of the book
Two Amazing concepts
Data and its types

2. Data Management and SPSS environment
Data Documentation Sheet
Introduction to SPSS
Data entry and transfer
Data transformation

3. Statistical tests of significance
Steps of hypothesis testing
Sampling errors
Types of statistical tests
Choosing a statistical test
P-values and effect sizes

4. Parametric tests
Continuous outcomes
Parametric test assumptions
T tests
Independent t tests:
Paired t test
ANOVA
RMANOVA

5. Non-parametric tests
Ordinal and Non-normal continuous outcomes
Mann Whitney U test
Wilcoxon Signed rank sum test
Non-parametric test with more than two comparison groups
Kruskal Wallis test
Friedman test

6. Correlation
Continuous outcomes
Correlation versus Association
Pearson’s correlation test
Spearman’s correlation test
Correlation versus Concordance
Measuring agreement or replaceability: Kendall’s τ vs Kendall’s W versus κ test

7. Categorical Variables
Introduction
Independent exposure variables
Chi Square test
Measuring the Strength of association of categorical variables
McNemar’s Chi Square test
Cochran Q test

8. Testing for Validity
Diagnostic Accuracy indices
Categorical data validity
Continuous data validity (ROC)

9. Testing for Reliability and Agreements
Inter-rater/Methods agreements in categorical data
Cohen’s Kappa test
Fleiss Kappa test
Inter-rater/Methods agreements in continuous data (Reliability tests)
Cronbach’s Alpha

10. Survival Analysis
Introduction
Lead time bias
Kaplan-Meier plot with log-rank
Cox Regression

11. Multivariate Analysis
Introduction
Linear Regression
Ordinal Regression
Logistic Regression

12. Annexures
Effect Size for statistical tests
How to use this book effectively
Proposed agenda for training
Reporting style of statistical tests
SAMPL guidelines