[R] Trouble Computing Type III SS in a Cox Regression
pjmiller_57 at yahoo.com
Fri Apr 26 14:19:54 CEST 2013
Date: Fri, 26 Apr 2013 10:13:52 +1200
From: Rolf Turner <rolf.turner at xtra.co.nz>
To: Terry Therneau <therneau at mayo.edu>
Cc: r-help at r-project.org, Achim Zeileis <Achim.Zeileis at uibk.ac.at>
Subject: Re: [R] Trouble Computing Type III SS in a Cox Regression
Message-ID: <5179AAA0.8060502 at xtra.co.nz>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
On 26/04/13 03:40, Terry Therneau wrote:
(In response to a question about computing "type III sums of squares in a
> If you have customers who think that the earth is flat, global warming
> is a conspiracy, or that type III has special meaning this is a
> re-education issue, and I can't much help with that.
--- On Thu, 4/25/13, Terry Therneau <therneau at mayo.edu> wrote:
> From: Terry Therneau <therneau at mayo.edu>
> Subject: Re: Trouble Computing Type III SS in a Cox Regression
> To: "Paul Miller" <pjmiller_57 at yahoo.com>, r-help at R-project.org
> Received: Thursday, April 25, 2013, 10:40 AM
> You've missed the point of my earlier
> post, which is that "type III" is not an answerable
> 1. There are lots of ways to compare Cox
> models, LRT is normally considered the most reliable by
> serious authors. There is usually not much difference
> between score, Wald, and LRT tests though, and the other two
> are more convenient in many situations.
> 2. "Type III" is a question that can't be
> addressed. SAS prints something out with that label, but
> since they don't document what it is, and people with
> in-depth knowlegde of Cox models (like me) cannot figure out
> what a sensible definition could actually be, there is
> nowhere to go. "How to do this in R" can't be
> answered. (It has nothing to do with interactions.)
> 3. If you have customers who think that the earth is
> flat, global warming is a conspiracy, or that type III has
> special meaning this is a re-education issue, and I can't
> much help with that.
> Terry T.
> On 04/25/2013 07:59 AM, Paul Miller wrote
> > Hi Dr. Therneau,
> > Thanks for your reply to my question. I'm aware that
> many on the list do not like type III SS. I'm not
> particularly attached to the idea of using them but often
> produce output for others who see value in type III SS.
> > You mention the problems with type III SS when testing
> interactions. I don't think we'll be doing that here though.
> So my type III SS could just as easily be called type II SS
> I think. If the SS I'm calculating are essentially type II
> SS, is that still problematic for a Cox model?
> > People using type III SS generally want a measure of
> whether or not a variable is contributing something to their
> model or if it could just as easily be discarded. Is there a
> better way of addressing this question than by using type
> III (or perhaps type II) SS?
> > A series of model comparisons using a LRT might be the
> answer. If it is, is there an efficient way of implementing
> this approach when there are many predictors? Another
> approach might be to run models through step or stepAIC in
> order to determine which predictors are useful and to
> discard the rest. Is that likely to be any good?
> > Thanks,
> > Paul
More information about the R-help