{smcl}
{hline}
help for {hi:nlhockey}
{hline}
{title:"Hockey Stick" Regression}
{p 4 8 2}
{cmd:nl hockey}
{it:yvar}
{it:xvar1}
[{it:xvarlist}]
[, {cmdab:l:eft0} {cmdab:r:ight0}]
{title:Description}
{p 4 4 2}
This command uses piecewise linear or "hockey stick" regression. It
assumes that the effect of {it:xvar1} can best be
fitted by two straight lines, with different slopes, and calculates
the two slopes and the value of {it:xvar1} at which the slope changes
(the breakpoint).
{title:Options}
{p 4 8}
{cmdab:r:ight0} constrains the slope to the right of the breakpoint to
be 0.
{p_end}
{p 4 8}
{cmdab:l:eft0} constrains the slope to the left of the breakpoint to
be 0.
{p_end}
{title:Remarks}
{p 4}
If called with just {it:yvar} and {it:xvar1}, {cmd:nlhockey} fits the model
{centre:{it:yvar} = a + b*{it:xvar1} if {it:xvar1} <= c}
{centre:{it:yvar} = d + e*{it:xvar1} if {it:xvar1} >= c}
{p}
This model requires 5 parameters, but since we want the two lines to
meet when {it:xvar1} = c, there is a constraint on the parameters
{centre:a + b*c = d + e*c}
{p}
so the model has only 4 degrees of freedom. The parameters estimated
by the model are a, b, c and e: if d is of interest it must be
calculated from the other parameters. In the output of nlhockey, the
three parameters relating to {it:xvar1} (c, b and e) are given first,
called breakpoint, slope_l and slope_r respectively. Then any
coefficients for variables in {it:xvarlist}, and finally parameter a
(called cons).
{p 4}
If {it:varlist} is included in the model, it is assumed that there
is a linear association between these variables and {it:yvar}, so
the models fitted become
{centre:{it:yvar} = a + b*{it:xvar1} + f*{it:xvar2} if {it:xvar1} <= c}
{centre:{it:yvar} = d + e*{it:xvar1} + f*{it:xvar2} if {it:xvar1} >= c}
{p}
i.e. only one extra parameter is estimated for each of these variables.
{p 4}
There is a short quadratic section between the two straight lines,
to ensure that the derivative of the predictor function w.r.t
{it:xvar1} is continuous at the break point. By
default, the width of this quadratic section is 1/100 times the
range of {it:xvar1}, but it can be changed by
setting the global variable $eps.
{p 4}
The options {cmd:left0} and {cmd:right0} force the constraints b = 0
and e = 0 respectively. Specifying both of these options is an
error. Also, specifying either of them inappropriately can lead to odd
results: if {cmd:left0} is specified and the slope for small values of
{it:xvar1} is non-zero, the breakpoint c may be set less than the
minimum value of {it:xvar1} in the dataset. The model is then no
longer identified: for any given breakpoint, there is an intercept a
which gives exactly the same model a simple linear regression. You
should run {cmd:loghockey} without either of these options first, and
only if the parameter estimates and standard errors from this model
convince you should you specify either of these options.
{title:References}
{p 4 }
The code in nlhockey.ado is based very closely on the Splus code by
Mary Lindstrom that was posted to the S-news mailing list, April 24,
2000. Also see
{p}
Bacon & Watts
"{it:Estimating the Transition Between Two Intersecting Straight Lines}",
Biometrika, 1971.
{title:Author}
{p 4 4 2}
Mark Lunt, Arthritis Research UK Epidemiology Unit
{p 4 4 2}
The University of Manchester
{p 4 4 2}
Please email {browse "mailto:mark.lunt@manchester.ac.uk":mark.lunt@manchester.ac.uk} if you encounter problems with this program.