SingVarIntSummaries {bkmr} | R Documentation |
Compare the single-predictor health risks when all of the other predictors in Z are fixed to their a specific quantile to when all of the other predictors in Z are fixed to their a second specific quantile.
SingVarIntSummaries(fit, y = NULL, Z = NULL, X = NULL, which.z = 1:ncol(Z), qs.diff = c(0.25, 0.75), qs.fixed = c(0.25, 0.75), method = "approx", sel = NULL, z.names = colnames(Z), ...)
fit |
An object containing the results returned by a the |
y |
a vector of outcome data of length |
Z |
an |
X |
an |
which.z |
vector indicating which variables (columns of |
qs.diff |
vector indicating the two quantiles at which to compute the single-predictor risk summary |
qs.fixed |
vector indicating the two quantiles at which to fix all of the remaining exposures in |
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; see details |
sel |
logical expression indicating samples to keep; defaults to keeping the second half of all samples |
z.names |
optional vector of names for the columns of |
... |
other argumentd to pass on to the prediction function |
If method == "approx"
then calls the function ComputePostmeanHnew.approx
. In this case, the argument sel
defaults to the second half of the MCMC iterations.
If method == "exact"
then calls the function ComputePostmeanHnew.exact
. In this case, the argument sel
defaults to keeping every 10 iterations after dropping the first 50% of samples, or if this results in fewer than 100 iterations, than 100 iterations are kept
For guided examples and additional information, go to https://jenfb.github.io/bkmr/overview.html