I prefer to think of ANOVA as a model comparison process.  The process requires 
calculating SS for various parts, or course.  But to me, how the process is 
carried out is important.  While some prefer to have SS for model terms that 
remain consistent with respect to the other terms in the model (type 3 SS), my 
preference is that the sum of the term SS equals the model SS (type 1 SS), 
consistent with Dean’s explanation in this thread.  This can probably be viewed 
as nothing more than a personal preference, but I will expand on this for the 
benefit of Morphmet readers who might not fully understand the logic.

It is perhaps unfortunate that ANOVA tables are as simple as they are typically 
presented.  For example, with a factorial model, Y ~ A + B + AB, the sources of 
variation found in an ANOVA table are listed as A, B, and AB (or A:B for the 
interaction) and SS are provided.  It might be more appropriate to describe the 
conditions.  For type 3 SS the SS are SS(A|B,AB), SS(B|A,AB), and SS(AB|A,B); 
for type 1 SS the SS are SS(A|intercept), SS(B|A), and SS(AB|A,B); and for the 
sake of comprehensiveness, for type 2 SS the SS are SS(A|B), SS(B|A), and 
SS(AB|A,B).  As Dr. Rohlf pointed out, for type 1 SS, the tests of effects can 
be viewed as arbitrary, because the model Y ~ B + A + AB will produce different 
SS for A and B because the sequence with which effects are introduced is 
different.  However, I would argue that SS(B|A) and SS(A|B) are two different 
things, and type 2 SS is (in part) tantamount to doing type 1 SS with different 
combinations of term order.  (I.e., type 2 SS tests the “main" effects given 
that other main effects are in the model, which for two-factor factorial 
models, is the second effect of type 1 SS for the two different orders of 
introduction of main effects.)

If the interaction is “significant”, it becomes sort of a moot argument, as all 
three approaches have the same conditional format, and focusing on main effects 
is probably ill-advised.  If the interaction is not significant, and is removed 
from the model, then types 2 and 3 SS are the same, and both are the same as 
type 1 SS run in both orders, focusing on the second effect in the process.  A 
debate about which is better can be had for this situation.  But if it comes to 
a default course of action for a program, here is why I am uncomfortable with 
type 3 SS.  The SS for both of the main effects are SS(A|B, AB) and SS(B|A,AB). 
 That is, e.g., SS(A|B, AB) (usually referred to simply as SSA) is found by 
calculating SSE(B,AB) - SSE(A,B,AB), where SSE is the summed squared error 
(residuals) for the models.  This does not make much sense to me.  To evaluate 
the effect, A, the model comparison uses a model that includes the interaction 
between A and B, but not one of the factors that is part of the interaction.  
This does not happen with type 1 or type 2 SS.

I found a blog that does a pretty good job explaining this in more detail, plus 
demonstrates how to appropriately alter design matrices for type 3 SS in R, 
when using aov: 
https://mcfromnz.wordpress.com/2011/03/02/anova-type-iiiiii-ss-explained/

Again, in geomorph, one can perform type 2 and type 3 SS calculations 
(advanced.procD.lm accommodates this).  I would like to add that 
advanced.procD.lm will also allow input of design matrices, which means one can 
use the model.matrix function with various contrasts to appropriately set up 
calculation of SS.  The program is quite flexible this way.  Understanding the 
process to calculate SS by model comparisons means one can choose the SS 
paradigm that is most appropriate for the research design and philosophical 
leaning.

Cheers!
-Mike

Michael Collyer

Associate Professor
Biostatistics
Department of Biology
Western Kentucky University
1906 College Heights Blvd. #11080
Bowling Green, KY 42101-1080
Phone: 270-745-8765; Fax: 270-745-6856
Email: [email protected]<mailto:[email protected]>

On Jul 10, 2015, at 10:31 PM, F. James Rohlf 
<[email protected]<mailto:[email protected]>> wrote:

I don’t understand your objections to type 3 SS. The fact they do not add up 
for unbalanced designs is because the effects are correlated. Type 3 allows one 
to test an effect with the other correlated factors held constant. Each SS is 
adjusted for all other factors.  It just tries to estimate what one would get 
if you had a proper balanced design. Being dependent on order makes the testing 
more arbitrary. It also adds the complexity that the SS are adjusted for the 
factors already tested and factors you will add later are ignored at that 
point. Testing in a different order my look like they give a different result 
(though not really because different things are being tested.

Philosophically, one could decide that the whole idea of “significance testing” 
is not useful but that is a different issue.
----------------------
F. James Rohlf, Distinguished Professor Emeritus, Dept. of Ecol. & Evol.
Research Professor, Dept. of Anthropology
Stony Brook University
The much revised 4th editions of Biometry and Statistical Tables are now 
available:
http://www.whfreeman.com/Catalog/product/biometry-fourthedition-sokal
http://www.whfreeman.com/Catalog/product/statisticaltables-fourthedition-rohlf
P Please consider the environment before printing this email

From: Collyer, Michael [mailto:[email protected]]
Sent: Thursday, July 9, 2015 12:56 PM
To: Waldir Miron; MORPHMET
Subject: [MORPHMET] Re: [geomorph] New comment on ANOVAs and Geomorph.

Dear Waldir,

There are both philosophical and practical reasons we do not now or will not 
offer options for choice of sums of squares in procD.lm.  First the practical 
reasons.  It is not trivial to offer such an option. The various sums of 
squares (types 1, 2, 3, etc.) all involve a paradigm of model comparisons. (We 
have a couple of blog posts about this on 
www.geomorph.net<http://www.geomorph.net/>.). If one understands the paradigms, 
advanced.procD.lm allows one to calculate any type of sums of squares (SS).  If 
you are determined to use type 3 SS, I recommend using advanced.procD.lm.

As for the philosophical reason that type 3 SS is not something we offer, it is 
a paradigm we choose not to acknowledge as valid. The reason for this is 
simple. With type 3 SS the sum of the parts exceeds the total. Type 3 SS, as a 
paradigm, involves removing effects from the "full" model, one by one, and 
calculating the changes in summed squared residuals as the effect SS. For 
unbalanced designs, the sum of SS across effects will exceed the model SS. This 
does not make much sense. Furthermore, the process involves removing main 
effects but retaining any interaction with these effects for calculating SS. 
This is a bit silly. Type 2 SS avoids this problem, and again, 
advanced.procD.lm can accommodate the type 2 approach.

By contrast, type 1 SS involves sequentially adding model effects and 
calculating the change in summed squared residuals as the effect SS. The sum of 
SS across the effects is the same as the full model SS. The order of effects is 
important, but we feel the biologist should have some cognizance of the 
appropriate order.

Because geomorph is an R package, users are free to manipulate functions. Thus, 
it is possible to augment the R script to provide type 3 SS. But this not 
something we will do as a permanent fixture, for the reasons above.

Good luck!

Mike Collyer

Sent from my iPhone

On Jul 9, 2015, at 9:35 AM, Waldir Miron 
<[email protected]<mailto:[email protected]>> wrote:
Waldir Miron<http://www.blogger.com/profile/10564967218097034020> has left a 
new comment on your post "ANOVAs and 
Geomorph<http://www.geomorph.net/2015/04/anovas-and-geomorph.html>":

Dear (s),

I am investigating fish shape variaton from different rivers basins and 
habitats within river basins. However, I have an unbalaced samples for both 
factors, it is recommended to do an Anova with SS error type III (marginal), to 
avoid some sampling bias.

Unfortunately, I tried several times but I was not able to calculate SS type 
III using the Procrustes coordinates with the procD.lm function from geomorph 
package. It seems that the default type error of the function is the type I, 
and I would like to know if there is any argument to change that or a way to do 
it. I would appreciate any help.

Regards.



Posted by Waldir Miron to geomorph<http://www.geomorph.net/> at July 9, 2015 at 
9:35 AM
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