SingVarRiskSummaries {bkmr}R Documentation

Single Variable Risk Summaries

Description

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)

Usage

SingVarRiskSummaries(fit, y = NULL, Z = NULL, X = NULL,
  which.z = 1:ncol(Z), qs.diff = c(0.25, 0.75), q.fixed = c(0.25, 0.5,
  0.75), method = "approx", sel = NULL, z.names = colnames(Z), ...)

Arguments

fit

An object containing the results returned by a the kmbayes function

y

a vector of outcome data of length n.

Z

an n-by-M matrix of predictor variables to be included in the h function. Each row represents an observation and each column represents an predictor.

X

an n-by-K matrix of covariate data where each row represents an observation and each column represents a covariate. Should not contain an intercept column.

which.z

vector indicating which variables (columns of Z) for which the summary should be computed

qs.diff

vector indicating the two quantiles q_1 and q_2 at which to compute h(z_{q2}) - h(z_{q1})

q.fixed

vector of quantiles at which to fix the remaining predictors in Z

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 z

...

other argumentd to pass on to the prediction function

Details

For guided examples and additional information, go to https://jenfb.github.io/bkmr/overview.html


[Package bkmr version 0.2.0 Index]