Plot bivariate predictor-response function on a new grid of points for MI BKMR

PredictorResponseBivarPair.MI(
  fit,
  y,
  Z,
  X,
  whichz1 = 1,
  whichz2 = 2,
  whichz3 = NULL,
  method = "approx",
  prob = 0.5,
  q.fixed = 0.5,
  sel = NULL,
  ngrid = 50,
  min.plot.dist = 0.5,
  center = TRUE,
  Z.MI,
  ...
)

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.
whichz1: vector identifying the first predictor that (column of Z) should be plotted
whichz2: vector identifying the second predictor that (column of Z) should be plotted
whichz3: vector identifying the third predictor that will be set to a pre-specified fixed quantile (determined by prob)
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
prob: pre-specified quantile to set the third predictor (determined by whichz3); defaults to 0.5 (50th percentile)
q.fixed: vector of quantiles at which to fix the remaining predictors in Z
sel: logical expression indicating samples to keep; defaults to keeping the second half of all samples
ngrid: number of grid points to cover the range of each predictor (column in Z)
min.plot.dist: specifies a minimum distance that a new grid point needs to be from an observed data point in order to compute the prediction; points further than this will not be computed
center: flag for whether to scale the exposure-response function to have mean zero
Z.MI: Multiple Imputed Z
...: other arguments to pass on to the prediction function

Value

a data frame with value of the first predictor, the value of the second predictor, the posterior mean estimate, and the posterior standard deviation