Single Variable Risk Summaries Compute summaries of the risks associated with a change in a single variable in Z from a single level (quantile) to a second level (quantile), for the other variables in Z fixed to a specific level (quantile)

Single Variable Risk Summaries Compute summaries of the risks associated with a change in a single variable in Z from a single level (quantile) to a second level (quantile), for the other variables in Z fixed to a specific level (quantile)

CDESingVarRiskSummaries.CMA(
  BKMRfits,
  e.y = NULL,
  e.y.names = NULL,
  which.z = 1:ncol(BKMRfits$Z),
  z.names = NULL,
  m.value = NULL,
  m.quant = c(0.1, 0.5, 0.75),
  m.name,
  qs.diff = c(0.25, 0.75),
  q.fixed = c(0.25, 0.5, 0.75),
  alpha = 0.05,
  sel,
  seed = 122
)

Arguments

BKMRfits: An object contatinint the results return by the kmbayes function
e.y: effect modifier for the outcome variable
e.y.names: column name of the effect modifier for the outcome variable
which.z: vector indicating which variables (columns of Z) for which the summary should be computed
z.names: optional vector of names for the columns of z
m.value: values that the mediator is set to
m.quant: values of the quantile that the mediator is set to
m.name: column name of the mediator
qs.diff: vector indicating the two quantiles q_1 and q_2 at which to compute h(z_q2)-h(z_q1)
q.fixed: a second quantile at which to compare the estimated h function
alpha: 1-confidence interval
sel: a vector selecting which iterations of the fit should be retained or inference
seed: the random seed to use to evaluate the code

Value

a data frame containing the (posterior mean) estimate and posterior standard deviation of the singlepredictor CDE risk measures

Details

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