Statalist The Stata Listserver


[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

Re: st: "alternative" stepwise approaches: Hierachical and Mixed


From   Richard Williams <[email protected]>
To   [email protected]
Subject   Re: st: "alternative" stepwise approaches: Hierachical and Mixed
Date   Fri, 26 Jan 2007 15:42:50 -0500

At 02:09 PM 1/26/2007, Diego Bellavia wrote:
1) Mixed approach: I have read some paper (clinical research) using thi s approach and I tried to get it in STATA
using :

sw outcome var1 var2 var3 var4, pe (0.1) pr (p 0.2)

The command works fine only when pe is less than pr. I sayd it works but I do not understand if it is a "mixed" stepwise approach
and actually, what is a "mixed" approach. Anyone can explain what are the different steps in such an approach ? Finally, when the "mixed" approach is better
than the standard backward (forward) one ?
I don't know how the papers you read defined "mixed", but what you are doing here is alternating between removing variables and adding them. The reference manual discusses this in more detail than the online help does. If I understand it correctly, the estimation begins with all variables included and then backwards selection is used to eliminate vars. Then, it switches to forward selection to add vars back in. Then, it goes back to backwards. The process stops once no more vars are either added or removed. (Unless maybe it gets into some sort of infinite loop!).

I believe the idea is that a var might be insignificant and get dropped; but once other vars have been dropped, it might become significant and qualify for re-inclusion. Or conversely, something might be significant and make it in, but once other vars are added it can become insignificant and should be dropped.

If you add the forward option, it will start with forward selection and then switch to backward.

When should you use the "mixed" approach? I guess if you want to be as mindlessly atheoretical as possible, "mixed" is even better than straight forward or backwards selection. stepwise approaches in general don't attract high praise, although i think they sometimes can have a little merit (e.g. it can be nice to see if a mindless atheoretical model comes out the same as or close to the model you derived theoretically).


2) Hierarchical stepwise: using the "hier" option, it works fine, but, again, it is not really clear to me what is the meaning of a hierarchical
model building, in what it is different, for example, to a standard backward/forward approach, and what STATA does during the different steps.
I have read something about the hierarchical model building technique, but the material I have found on-line were not that clear.
In your first example it wouldn't matter whether you list the vars as x1 x2 x3 x4 or if you listed them as x3 x4 x1 x2, i.e. order wouldn't matter. It would matter if using hierarchical. So yes, I suppose you could have your interaction terms listed last, and if using backwards hierarchical, it would begin by testing whether the interactions belong in the model. If they are significant, the process stops. If not significant, then it would go to your next term or set of terms (in the order you listed them), and test it/them. Process stops once the term/terms test is/are significant.

Or, if you use forward hierarchical, it tests to see if the first term should make it in. If no, the process stops and it goes to the next term and repeats the process.

Note that you can group vars, if the var list is x1 x2 (x3 x4 x5) then x3 x4 x5 will be tested simultaneously, e.g. you might group your interaction terms that way.

The hierarchical approach is, or can be, fairly theoretical. You can get much the same thing using -nestreg- though.


-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
FAX: (574)288-4373
HOME: (574)289-5227
EMAIL: [email protected]
WWW (personal): http://www.nd.edu/~rwilliam
WWW (department): http://www.nd.edu/~soc
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/




© Copyright 1996–2024 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index