**Example (SAS
program strtxmpl1.sas):
using start values to adjust group trajectories. This example shows how to
create starting values to make adjustments to a trajectory model. **

**
We'll use opposition behavior data (scale - 0 to 10) from the Montreal
Longitudinal Study. **

**The
strategy used here is to start with all cubic trajectories. **

**The
order for each group is decreased so that the highest order parameter estimates
(for trajectories beyond intercept only), are significant for each group.**

**Step
1: Fit the cubic trajectory model.**

**
Three-group cubic trajectory model : The log shows the default start values.**

**
Three-group cubic trajectory model
results.**

**In
group 1, the slope parameter is the highest significant term (p = 0.0406).
**

**In
group 2, the cubic parameter (p = 0.0037) is the highest significant term, while
in group 3, the quadratic term (p < 0.00005) is the highest significant term.
**

**So the
appropriate orders are 1 3 2. **

**The log has the
parameter estimate column from the output
to ease cutting and pasting into the SAS program to create start values.**

**
Parameter estimates are given in the log for cut and paste.**

**Step
2: Create start values from the first model results.**

**
We're going to eliminate terms from the initial model. **

**The
parameter estimates from the initial model are copied from the log. **

**
Since this example does not use risk factors, the second set of parameter
estimates are used. **

**
Eliminated parameters have been commented out as shown below.**

**
Modified three-group model with start values.**

**
Final three-group model results.**

**
SAS program:
strtxmpl1.sas**

**
**