Calculate overall risk summaries when fixing multiple effect modifiers at certain levels

OverallRiskSummaries.fixEY(
  list.fit.y.TE,
  qs = seq(0.25, 0.75, by = 0.05),
  q.fixed = 0.5,
  q.alwaysfixed = NULL,
  EY.alwaysfixed.name = NULL,
  sel = NULL,
  method = "approx"
)

Arguments

list.fit.y.TE: The Total Effect BKMR model fit in a 'List' form.
qs: vector of quantiles at which to calculate the overall risk summary
q.fixed: a second quantile at which to compare the estimated h function
q.alwaysfixed: the quantile values in the point which we want to keep fixed for all comparisons
EY.alwaysfixed.name: names of all the effect modifiers that we want to fixed for all comparisons
sel: selects which iterations of the MCMC sampler to use for inference
method: method for obtaining posterior summaries at a vector of new points. Options are"approx" and "exact"; defaults to "approx", which is faster particularly for large datasets

Value

a list of data frame containing the (posterior mean) estimate and posterior standard deviation of the overall risk measures, for each of the comparisons specified

Details

For guided examples, go to https://zc2326.github.io/causalbkmr/articles/BKMRCMA_Effectof_singleZ.html