vpc_opt | R Documentation |
Provide a list of options to vpc_data
function.
vpc_opt(
bins = "jenks",
n_bins = "auto",
bin_mid = "mean",
pred_corr = FALSE,
pred_corr_lower_bnd = 0,
pi = c(0.025, 0.975),
ci = c(0.025, 0.975),
lloq = NULL,
uloq = NULL,
rtte = FALSE,
rtte_calc_diff = TRUE,
events = NULL,
kmmc = NULL,
reverse_prob = FALSE,
as_percentage = TRUE
)
bins |
Binning method, can be one of 'density', 'time', 'data', 'none', or one of the approaches
available in |
n_bins |
When using the 'auto' binning method, what number of bins to aim for. |
bin_mid |
Specify how to is the mid bin value calculated, can be either 'mean' for the mean of all timepoints (default) or 'middle' to use the average of the bin boundaries. |
pred_corr |
Option reserved to continuous VPC. Logical, should a prediction correction (pcVPC) of the data be used. |
pred_corr_lower_bnd |
Option reserved to continuous VPC. Lower bound for the prediction-correction. |
pi |
Option reserved to continuous VPC. Simulated prediction interval to plot. Default is c(0.05, 0.95). |
ci |
Confidence interval around the percentiles to plot. Default is c(0.05, 0.95) |
lloq |
Number or NULL indicating lower limit of quantification. Default is NULL. |
uloq |
Number or NULL indicating upper limit of quantification. Default is NULL. |
rtte |
Option reserved to time-to-event VPC. Is the data repeated time-to-event (RTTE) |
rtte_calc_diff |
Option reserved to time-to-event VPC. Should the time be recalculated? When simulating in NONMEM,
you will probably need to set this to |
events |
Option reserved to time-to-event VPC. Numeric vector describing which events to show a VPC for when
repeated TTE data, e.g. c(1:4). Default is |
kmmc |
Option reserved to time-to-event VPC. Either NULL for regular TTE VPC (default), or a variable name for a KMMC plot (e.g. 'WT'). |
reverse_prob |
Option reserved to time-to-event VPC. Should the probability be reversed (i.e. plot 1-probability). |
as_percentage |
Should the Y-scale be in percent (0-100) |
vpc
vpc_data
vpc_opt()
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