3 papers
stat.ME2026
Don't Disregard the Data for Lack of a Likelihood: Bayesian Synthetic Likelihood for Enhanced Multilevel Network Meta-Regression
Harlan Campbell, Charles C. Margossian, Jeroen P. Jansen +1
Multilevel network meta-regression (ML-NMR) enables population-adjusted indirect treatment comparisons by combining individual patient data (IPD) with aggregate data. When individu…
stat.ME2025
A fully Bayesian approach for the imputation and analysis of derived outcome variables with missingness
Harlan Campbell, Tim Morris, Paul Gustafson
Derived variables are variables that are constructed from one or more source variables through established mathematical operations or algorithms. For example, body mass index (BMI)…
stat.ME2024
Integrating representative and non-representative survey data for efficient inference
Nathaniel Dyrkton, Paul Gustafson, Harlan Campbell
Non-representative surveys are commonly used and widely available but suffer from selection bias that generally cannot be entirely eliminated using weighting techniques. Instead, w…