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An appropriate analysis must take into account the amount of data available for analysis. For continuous outcomes, this may involve the number of individuals with baseline covariates and primary outcomes, while binary and time to events may additionally depend on the number of observed events. plot_outcome_counts provides a way to visualize the amount of data available for analysis.

Usage

plot_outcome_counts(
  prepared_data,
  study_time = NULL,
  type = "tc",
  count_increment = 10,
  time_increment = 30,
  color_palette = NULL
)

Arguments

prepared_data

A prepeared dataset: see prepare_monitored_study_data

study_time

A numeric scalar indicating the study time at which the data should be reconstructed and events should be counted

type

A character scalar containing "t" for the total number of observations, "c" for the number of complete observations, and "e" for the number of events (for time-to-event or binary outcomes)

count_increment

Plots have horizontal lines at regular increments to assist in reading of counts. count_increment is a numeric scalar indicating the increment between horizontal lines on the count axis.

time_increment

Plots have horizontal lines at regular increments to assist in reading of counts. time_increment is a numeric scalar indicating the increment between vertical lines on the time axis.

color_palette

A vector of colors for each event.

Examples

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