Hi All

I've run the follwoing mixed effects model with linear splines to look at change in multimorbidity in individuals over time (4 splines for 4 periods: wave1 = 1982-1989, wave2 = 1989-1999, wave3 = 1999-2009 & wave4= 2009-2015):


Code:
mkspline wave1 1 wave2 2 wave3 3 wave4 = wavex

tablist wavex wave1 wave2 wave3 wave4, sort(v)
The mixed effects model (growth curve analysis with linear splines):

Code:
mixed score wave1 wave2 wave3 wave4 sex || NSHD_ID: wavex, cov(unstr) mle stddev
(wavex is coded as 0, 1, 2, 3 & 4)


The model:

Computing standard errors:

Mixed-effects ML regression Number of obs = 18,615
Group variable: NSHD_ID Number of groups = 3,723

Obs per group:
min = 5
avg = 5.0
max = 5

Wald chi2(5) = 2057.52
Log likelihood = -29275.269 Prob > chi2 = 0.0000

------------------------------------------------------------------------------
score | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
wave1 | .4517862 .0221717 20.38 0.000 .4083305 .4952419
wave2 | .3639538 .0221717 16.42 0.000 .3204981 .4074095
wave3 | .2409347 .0221717 10.87 0.000 .197479 .2843904
wave4 | .4963739 .0221717 22.39 0.000 .4529182 .5398296
|
sex |
Female 2547 | .1654415 .0260374 6.35 0.000 .1144092 .2164739
_cons | .5049936 .0215023 23.49 0.000 .4628498 .5471374
------------------------------------------------------------------------------

------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
NSHD_ID: Unstructured |
sd(wavex) | .4243546 .0072879 .4103083 .4388818
sd(_cons) | .5270375 .0181214 .4926906 .5637788
corr(wavex,_cons) | -.1251645 .033656 -.1904833 -.0587422
-----------------------------+------------------------------------------------
sd(Residual) | .9083197 .0060774 .896486 .9203096
------------------------------------------------------------------------------
LR test vs. linear model: chi2(3) = 7825.50 Prob > chi2 = 0.0000



I generally use margins & marginsplot to graph results from mixed-effects modelling, but I'm running into issues. So in the interest of time as I need to get a poster ready, I'm trying to use graph tw for this particular model. However, I'm a bit unsure about the details of the syntax. I'm trying to plot a graph which will show two lines (for males & females - males is the reference group in the above model) nut I'm unsure how to correctly specify the range. What I have so far :

Code:
tw  (function y=.5049+0.45+0.36+.24+.49*x, range(0 1 2 3 4) color(blue)) ///
    (function y=.5049+0.45+0.36+.24+.49+0.16, range(0 1 2 3 4) color(red)), ///
    name(sex, replace) legend(off)
Thanks
/Amal