Biostatistics that holds up
under review.

I’m Paulina Del Mundo: physician, MPH from Hopkins (epidemiology and biostatistics), clinical data scientist. I work with medical researchers, small companies, and nonprofits on study design, causal inference, sensitivity analysis, and methods writing rigorous enough to publish.

MD MPH Hopkins 24.6M+ encounters analyzed

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Design

Study design

Research-question framing, target trial emulation, study population, sample size and power, protocol writing.

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Analysis

Analysis methods

Causal inference (DiD, RDD, IV, synthetic control), propensity scores, survival analysis, longitudinal data, Monte Carlo simulation.

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Robustness

Sensitivity & robustness

Pre-specified sensitivity analyses, placebo and falsification tests, bias quantification (E-values, Rosenbaum bounds), unmeasured-confounding sensitivity.

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Writing

Methods writing

Methods sections for manuscripts, grants, IRB protocols, and regulatory submissions; reviewer responses on methodology.

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Chapter 1

From research question to study design

PICO/PECO framing, target trial emulation, primary-vs-secondary endpoint logic, pre-registration. A seven-step decision framework with worked examples.

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Chapter 3

Causal inference toolkit

DiD, RDD, IV, synthetic control, propensity-score methods. When each applies, what each assumes, how to defend it.

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Chapter 5

Monte Carlo simulation

When closed-form formulas don’t fit. Sample-size simulation, bias quantification, type-I error rate calibration, transparent reproducible reporting.

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Population epi

NHANES cardiometabolic risk

Survey-weighted analysis, MI, calibration vs AUC, structural-overlap diagnostics in a head-to-head with the Pooled Cohort Equations.

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Real-world data

Medicaid outlier detection

Robust statistics on heavy-tailed data, BH-FDR multiplicity, isolation-forest second opinion, ontology-aware claims-data analysis.

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Causal inference

Part D insulin DiD

A clean Inflation Reduction Act natural experiment: TWFE DiD, event-study, parallel-trends defense, placebo and leave-one-out robustness.

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All writing →