Single Variable Interaction Summaries

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Description

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.

Usage

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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),
  preds.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 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 Z

preds.method

method for obtaining posterior summaries at a vector of new point. Currently only implemented for preds.method = "approx"

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