Statistical Analysis
Baseline characteristics of patients were compared using Chi-Squared or
Fishers Exact tests. Q values were also computed for all variables
versus treatment status to account for the increased false discovery
rate due to multiple comparison in this analysis. Causal forests were
used to estimate conditional average treatment effects for each variable
for those treated and untreated with oseltamivir (6-9). These effects
were also accounting for all other variables under study via the random
forest approach and can be considered unbiased estimates of the absolute
effect of the oseltamivir therapy conditioned on membership in a
particular subgroup. For the causal forest, a total of 50,000 trees were
used to allow for accurate computation of 95% confidence intervals.
Conditional average treatment effects were extracted for each
categorical variable under consideration along with the 95% confidence
interval and a data visualization was created for each outcome. R v4.04
(R Foundation for Statistical Computing, Vienna, Austria) was used for
all analyses. The package grf was used for computation of causal
forests and extraction of conditional average treatment effects (10).