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Plotting controlled effect curves

Source: R/plots.R
plot_ce.Rd

Plot CR and/or CVE curves

Usage

plot_ce(
  ...,
  which = "CR",
  density_type = "none",
  dat = NA,
  dat_alt = NA,
  zoom_x = "zoom in",
  zoom_y = "zoom out",
  labels = NA
)

Arguments

...

One or more objects of class "vaccine_est" returned by est_ce.

which

One of c("CR", "CVE"); controls whether to plot CR curves or CVE curves.

density_type

One of c("none", "kde", "kde edge"). Controls the type of estimator used for the background marker density plot. For "none", no density plot is displayed. For "kde", a weighted kernel density estimator is used. For "kde edge", a modified version of "kde" is used that allows for a possible point mass at the left edge of the marker distribution.

dat

The data object originally passed into est_ce, used for plotting densities. It is only necessary to pass this in if density_type is not set to "none".

dat_alt

Alternative data object; a list containing one or more dataframes, each of the form data.frame(s=..., weights=...). Column s contains biomarker values and column weights contains corresponding two-phase sampling weights. This can be used as an alternative to specifying dat, and is particularly useful for plotting multiple densities on a single plot. If plotting multiple densities, the order of the dataframes should correspond to the order of "vaccine_est" objects passed in. See examples.

zoom_x

Either one of c("zoom in", "zoom out") or a vector of length 2. Controls the zooming on the X-axis. The default "zoom in" will set the zoom limits to the plot estimates. Choosing "zoom out" will set the zoom limits to show the entire distribution of the marker. Entering a vector of length 2 will set the left and right zoom limits explicitly.

zoom_y

Either "zoom out" or a vector of length 2. Controls the zooming on the Y-axis. The default "zoom out" will show the entire vertical range of the estimates. Entering a vector of length 2 will set the lower and upper zoom limits explicitly.

labels

A character vector of length equal to the length of list(...), representing plot labels. Only used if length(list(...))>1.

Value

A plot of CR/CVE estimates

Examples

# \donttest{
# Plot one curve
data(hvtn505)
dat <- load_data(time="HIVwk28preunblfu", event="HIVwk28preunbl", vacc="trt",
                 marker="IgG_V2", covariates=c("age","BMI","bhvrisk"),
                 weights="wt", ph2="casecontrol", data=hvtn505)
ests_cox <- est_ce(dat=dat, type="Cox", t_0=578)
plot_ce(ests_cox, density_type="kde", dat=dat)

# Trim display of plot according to quantiles of the biomarker distribution
ests_cox_tr <- trim(ests_cox, dat=dat, quantiles=c(0.05,0.95))
plot_ce(ests_cox_tr, density_type="kde", dat=dat)

# Plot multiple curves (same biomarker)
ests_np <- est_ce(dat=dat, type="NP", t_0=578)
plot_ce(ests_cox, ests_np, density_type="kde", dat=dat)

# Plot multiple curves (two different biomarkers)
dat2 <- load_data(time="HIVwk28preunblfu", event="HIVwk28preunbl", vacc="trt",
                  marker="IgG_env", covariates=c("age","BMI","bhvrisk"),
                  weights="wt", ph2="casecontrol", data=hvtn505)
ests_cox2 <- est_ce(dat=dat2, type="Cox", t_0=578)
dat_alt <- list(
  data.frame(s=dat$s[dat$a==1], weights=dat$weights[dat$a==1]),
  data.frame(s=dat2$s[dat2$a==1], weights=dat2$weights[dat2$a==1])
)
plot_ce(ests_cox, ests_cox2, density_type="kde", dat_alt=dat_alt)
# }