--- "A. Manzoni" <[email protected]> wrote:
> Here is my case: I want to model recall bias in retrospective
> surveys, looking at the length of the recall period (i.e. distance
> between the events reconstructed and the interview) and I was
> suggested to try to use a spline model.
>
> I have some theories concerning the shape of the recall (i.e. for
> example I may think that from 10 years onwards it doesn't make any
> difference how much the time distance to the interview is), but I
> know it should be somehow possible to get the number and the position
> of knots which better describe what's going on, besides the shape of
> the effect.
With splines there is a number of issues:
o the number of knots
o the location of the knots
o is the curve between knot linear or quadratic or cubic or...
A simple representation of your theory would be a linear spline with a
single knot at 10 years. You would make these variables like this:
mkspline yr1 10 yr2 = year
If your theory is true than you would expect that the coefficient of
yr2 is 0
An elaboration would be that you want to estimate where that knot is.
This was discussed in this post:
http://www.stata.com/statalist/archive/2008-01/msg01006.html
It may be that you just want to allow the effect of time to have some
flexible non-linear effect. In that case you could have a look at
Patrick Royston's -mvrs- command (see: -findit mvrs-), which is
described in (Royston and Sauerbrei 2007).
Hope this helps,
Maarten
Patrick Royston and Willi Sauerbrei (2007) "Multivariable modeling with
cubic regression splines: A principled approach". The Stata Journal,
7(1): 45-70.
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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