Joinpoint Trend Analysis

Fits a joinpoint (segmented log-linear) regression to a series of rates measured over time - the standard analysis for cancer-registry incidence and mortality trends. The number of joinpoints (change points in trend) is selected data-adaptively, and each segment is summarized by its Annual Percent Change (APC). The overall Average Annual Percent Change (AAPC) summarizes the whole period. Use it to detect when a rate began rising or falling and to quantify the rate of change in each period.

Usage

joinpoint(
  data,
  time,
  rate,
  maxJoinpoints = 3,
  conf_level = 0.95,
  showSegments = TRUE,
  showAAPC = TRUE,
  showPlot = TRUE,
  logScale = FALSE,
  showSummary = FALSE,
  showExplanation = FALSE
)

Arguments

data

The data as a data frame (one row per time point).

time

Time variable (e.g. calendar year).

rate

The rate or count measured at each time point. Modelled on the log scale, so all values must be positive.

maxJoinpoints

The maximum number of joinpoints (change points) to consider. The best number up to this maximum is selected using the Bayesian Information Criterion.

conf_level

Confidence level for APC / AAPC intervals.

showSegments

Report the Annual Percent Change for each fitted segment.

showAAPC

Report the Average Annual Percent Change over the whole period.

showPlot

Display the observed rates with the fitted joinpoint trend.

logScale

Plot the y-axis on a logarithmic scale (log-linear segments become straight).

showSummary

Display a plain-language summary of the trend.

showExplanation

Display an explanation of joinpoint regression.

Value

A results object containing:

results$todo					a html
results$joinpointTable					a table
results$segmentTable					a table
results$aapcTable					a table
results$plot					an image
results$summary					a html
results$explanation					a html

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$joinpointTable$asDF

as.data.frame(results$joinpointTable)

Examples

# \donttest{
joinpoint(
    data = mydata,
    time = "year",
    rate = "incidence_rate",
    maxJoinpoints = 3)
#> Error: object 'mydata' not found
# }