Clinical Data Analysis Pipeline

We provide rigorous biostatistical consulting tailored for medical theses, postgraduate dissertations, and peer-reviewed observational or interventional clinical studies. All analysis pipelines utilize standard analytical software including SPSS, R, and STATA to deliver publication-ready statistical outputs.

Core Analytical Methodologies

• Sample Size & Power Calculation: Precise determination of study sample sizes using G*Power and PASS software, ensuring adequate statistical power for hypothesis testing while avoiding over-sampling.

• Descriptive & Parametric/Non-Parametric Testing: Data distribution screening, normal distribution testing, Chi-Square, Independent t-tests, Mann-Whitney U, ANOVA, and Kruskal-Wallis analysis.

• Multivariate & Predictive Modeling: Logistic, linear, and ordinal regression modeling to adjust for confounding variables and identify independent clinical predictors.

• Survival & Diagnostic Accuracy Analysis: Kaplan-Meier survival curves, Cox proportional hazards models, ROC curve analysis, and diagnostic sensitivity/specificity calculations.

• Publication Visualizations: Formatted, high-resolution tables (APA/ICMJE style) and figures with accompanying technical statistical interpretations.