Joinpoint Regression Program
Latest Release: Version 3.3 (April 2008).
Joinpoint is statistical software for the analysis of trends using joinpoint models, that is, models like the figure
below where several different lines are connected together at the "joinpoints." Cancer trends reported in NCI publications
are calculated using the Joinpoint Regression Program to analyze rates calculated by the SEER*Stat
software. Methods & Software for Populationbased Cancer Statistics shows the relationship
of the Joinpoint Regression Program to SEER*Stat and other statistical methods and tools.
[D]
Sample Joinpoint Graph

The software takes trend data (e.g cancer rates) and fits the
simplest joinpoint model that the data allow. The user supplies
the minimum and maximum number of joinpoints. The program starts
with the minimum number of joinpoint (e.g. 0 joinpoints, which
is a straight line) and tests whether more joinpoints are statistically
significant and must be added to the model (up to that maximum
number). This enables the user to test that an apparent change
in trend is statistically significant. The tests of significance
use a Monte Carlo Permutation method. The models may incorporate
estimated variation for each point (e.g. when the responses are
age adjusted rates) or use a Poisson model of variation. In addition,
the models may also be linear on the log of the response (e.g.
for calculating annual percentage rate change). The software also
allows viewing one graph for each joinpoint model, from the model
with the minimum number of joinpoints to the model with maximum
number of joinpoints. For details see:
Kim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for
joinpoint regression with applications to cancer rates. Stat
Med 2000;19:33551 (correction: 2001;20:655).
Correction to Table 1(a) of Kim, et al. is provided as a PDF. Other references are available in the online help system.
As of version 3.3, an important new feature has been added to Joinpoint, the Average Annual Percent Change (AAPC). While Joinpoint computes the trend in segments whose start and end are determined to best fit the data, sometimes it is useful to summarize the trend over a fixed predetermined interval. The AAPC is a method which uses the underlying Joinpoint model to compute a summary measure over a fixed prespecified interval.
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