Define the unit of analysis
Distinguish a participant, trip, flight leg, and measurement. Build keys and eligibility rules before counting records or fitting models.
BIOSTATISTICS · DATA SCIENCE · RESEARCH SOFTWARE
I build statistical workflows that make the reasoning visible: how records are joined, how outcomes are defined, how models are checked, and where a result stops being certain.
Research portfolio based on reviewed university project materials. Raw participant data is excluded.
SELECTED WORK / 01—06
Each case study shows the question, the technical choices, the decision logic, and the checks that make the result interpretable.
THE ANALYTICAL METHOD
A credible analysis is a chain of decisions. I make each link inspectable, from the first source file to the final interpretation.
Distinguish a participant, trip, flight leg, and measurement. Build keys and eligibility rules before counting records or fitting models.
Normalize timestamps and time zones; join records across trips; derive sleep, performance, and schedule windows using documented boundaries.
Use survival analysis for time to recovery, mixed models for repeated observations, and descriptive comparisons when causal claims are unsupported.
Review missingness, residuals, proportional hazards, influential records, and source-to-output reconciliation before presenting a conclusion.
TOOLS & CAPABILITIES
Project technologies are separated from methods, so a tool name never stands in for an analytical result.
R · survival · lme4 · lmerTest · car · DHARMa · effectsize
dplyr · tidyr · purrr · lubridate · stringr · readxl · openxlsx
ggplot2 · Plotly · Shiny · shinydashboard · DT · R Markdown
Cox models · censoring · mixed-effects models · feature engineering · cohort checks · validation
SELECTED CERTIFICATIONS
Survival Analysis in R · SQL for Data Science · Intermediate Python · Joining Data with pandas
DataCamp, University of California Davis. Course credentials are shown separately from technologies evidenced in the research projects.LET’S TALK RESEARCH
These case studies make the project logic and evidence available for discussion without exposing participant-level research data.