----- Forwarded message from carlo.mel...@unina.it -----
Date: Tue, 23 Apr 2013 04:01:24 -0400
From: carlo.mel...@unina.it
Reply-To: carlo.mel...@unina.it
Subject: Re: Linear models for cranial variability
To: morphmet@morphometrics.org
Dear Milos,
you can try using Partial Least Square that allows to look at
correlation between one block of variables (cranial dimensions) and
the second block of variables (environmnetal variables). Make sure you
standardize the variables (e.g. for cranial dimension it would be good
using log transformation of measurements and for environmental data
try to standardize by subtracting mean so that data values are not too
disparate or large).
Alternatively, if you want to make predictions you can perform a
multiple multivariate regression or a Generalised Least Square model.
However, they have more assumption dealing with multivariate data
normality while PLS has not.
You can do PLS using the current version of the free software PAST
that has a user friendly interface. For multiple multivariate
regression and Generalised Least Square NTSYS or SPSS or specific
scripts in R.
All the best
Carlo Meloro
morphmet_modera...@morphometrics.org ha scritto:
>
>
> ----- Forwarded message from Milos Blagojevic -----
>
> Date: Mon, 22 Apr 2013 15:12:47 -0400
> From: Milos Blagojevic
> Reply-To: Milos Blagojevic
> Subject: Linear models for cranial variability
> To: "morphmet@morphometrics.org"
>
> Dear Morphometricians,
> Drifting a little bit from the field of GM I have a question about
> the formulation of a linear (or possible any other) model that has
> to account for cranial variability in relation to certain
> ecological parameters.
> My dataset consists of 50 linear measurements taken on roe deer
> skulls from 12 populations. After PCA and optional discriminant
> analysis I have individual scores that should enter possible linear
> model as dependent variables. Ecological data consists of
> proportions of forest to meadow to plowland areas (expressed either
> as proportions that add up to 1 or as absolute areas in Ha) within
> every population and population density (individual/area or
> absolute numbers). Any ideas on what kind of a model could be
> suitable for this dataset and for testing the hypothesis that
> cranial dimensions are predicted by these independent variables
> (habitat structure and abundance or population density)?
> Best regards,Milos BlagojevicDepartment for Biology and
> Ecology,Faculty of Science,Kragujevac,Serbia
> Here is sample data (with absolute numbers but they can be expressed
> as proportions as well)
> PCx score population abundance forest plow meadow -0.6033788
> ADA_BEC 1500 61154 12000 32313 0.3250981 ADA_BEC 1500
> 61154 12000 32313 0.5577059 ADA_BEC 1500 61154
> 12000 32313 -0.1596194 PM 23980 89499 579870 8178
> -1.3089952 PM 23980 89499 579870 8178 -2.1693392 SP
> 2500 38000 47098 432432 -0.9669080 SP 2500
> 38000 47098 432432 -1.8857842 SP 2500 38000 47098
> 432432 0.7242678 DKN 65908 181133 12400 1233
> 1.6815373 DKN 65908 181133 12400 1233
>
> ----- End forwarded message -----
>
>
>
>
----- End forwarded message -----
