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Longitudinal patient timeline (swimlane)

Source: R/timeline.R
longitudinalTimeline.Rd

Draws a longitudinal rehabilitation timeline: each outcome measure is a stacked lane showing its trajectory across sessions, intervention periods are shaded spans across all lanes, and points where the session-to-session change crosses the Minimal Detectable Change / Minimal Clinically Important Difference are marked (via annotateChange).

Usage

longitudinalTimeline(
  sessions,
  interventions = NULL,
  outcomes,
  mdc = NULL,
  mcid = NULL
)

Arguments

sessions

A data.frame of session timepoints with a time column (numeric or Date) and an optional label; drawn as light session reference lines.

interventions

Optional data.frame of intervention periods with start and end columns (and an optional label); drawn as shaded spans behind every lane.

outcomes

A long data.frame of outcome measurements with columns time, metric and value (one lane per metric).

mdc, mcid

Optional MDC / MCID thresholds used to flag crossings: a scalar applied to all metrics, or a value named by metric. Both must be supplied to draw crossing markers.

Value

A ggplot object (faceted, one lane per metric).

See also

annotateChange(), as.timelineData()

Examples

sessions <- data.frame(time = 1:5)
outcomes <- data.frame(time = rep(1:5, 2),
  metric = rep(c("gait_speed", "fma"), each = 5),
  value = c(0.6, 0.7, 0.9, 1.0, 1.1, 20, 22, 28, 30, 33))
longitudinalTimeline(sessions, outcomes = outcomes,
  mdc = c(gait_speed = 0.1, fma = 5), mcid = c(gait_speed = 0.15, fma = 9))