G*Power Analysis 2
Calculating Sample Size for Medical and Clinical Studies
Showcase
Biostatistics Projects
G*Power Analysis
Sample Size Calculation in Scientific Studies
ROC Curve for Diagnostic Test Evaluation
Measure and visualize test sensitivity, specificity, and overall accuracy using ROC metrics.
AUC-Based Model Comparison
Measuring the accuracy of machine learning models using the ROC curve area (AUC).
Post-Treatment Follow-Up with Kaplan-Meier
Comparative analysis of post-treatment survival expectations.
Kaplan-Meier Analysis on Clinical Data
Graphical and statistical comparison of survival times across different groups.
Prediction with Regression Models
Model relationships between numerical variables and make accurate predictions for the future.
Linear Regression for Analytical Interpretation
Analyzing meaningful relationships using statistical regression lines.
Multivariate Data Analysis
Advanced statistical evaluation of complex relationships between multiple variables.
A/B Testing Decision Support Tools
Measure performance with advanced multivariate testing across experimental groups.
Kaplan-Meier Survival Analysis in Clinical Research
Creation of survival curves with detailed assessment of treatment effects over time.
Kaplan Meier Analysis
Examples of survival analysis visualized with real datasets.
