Crossover Trial Design and Analysis
A comprehensive guide to crossover trial design and analysis, including 2×2 crossover studies, treatment and period effects, sequence effects, carryover, within-subject comparisons, mixed-effects models, sample size, missing data, and a complete worked example.
Companion Diagnostic Statistical Validation
A practical guide to statistical validation of companion diagnostics, covering analytical accuracy, precision, reproducibility, sensitivity, specificity, limit of detection, reportable range, interference, robustness, clinical concordance, positive and negative percent agreement, confidence intervals, sample size, missing data, discordant results, and regulatory considerations.
Cluster Randomized Trial Design
A computational guide to cluster randomized trial design, including intracluster correlation, design effects, unequal cluster sizes, effective sample size, sample size inflation, analysis considerations, and a complete worked example.
Building a Biostatistics Portfolio Project
A practical guide to building a biostatistics portfolio project, including project selection, clinical research questions, data preparation, statistical analysis plans, R programming, visualization, reproducibility, GitHub organization, validation, reporting, and interview presentation.
Blinded vs. Unblinded Data Review Best Practices
A detailed practical guide to blinded and unblinded data review in clinical trials, including roles, firewalls, review workflows, data listings, programming examples, validation, and database lock readiness.
Biostatistics Interview Questions and Answers
A comprehensive guide to biostatistics interview questions and answers, covering probability, hypothesis testing, confidence intervals, regression, survival analysis, clinical trials, missing data, CDISC, SAS, R, study design, statistical interpretation, and practical interview scenarios.
Biosimilar Statistical Assessment Requirements
A practical guide to statistical assessment requirements for biosimilar development, covering analytical similarity, quality attributes, acceptance ranges, PK and PD equivalence, clinical efficacy, immunogenicity, sample size, confidence intervals, FDA and EMA expectations, estimands, sensitivity analyses, and R implementation.
Biomarker-Stratified Trial Designs
A practical guide to biomarker-stratified clinical trial designs, including stratified randomization, biomarker subgroups, predictive versus prognostic biomarkers, enrichment designs, treatment-by-biomarker interaction, sample size, multiplicity, missing biomarker status, statistical analysis, regulatory interpretation, and R implementation.
Basket Trials in Oncology Research
A comprehensive guide to basket trials in oncology research, including biomarker-defined populations, multiple tumor types, independent and Bayesian hierarchical analyses, borrowing of information, multiplicity, operating characteristics, a complete worked example, and R implementation.
Alpha-Spending Functions: O’Brien-Fleming vs. Pocock
A practical guide to alpha-spending functions in group sequential clinical trials, comparing O