[R] Using the mahalanobis( ) function

From: Tyler Rinker <tyler_rinker_at_hotmail.com>
Date: Mon, 21 Mar 2011 20:33:58 -0400

Hello all,  

I am a 2 month newbie to R and am stumped. I have a data set that I've run multivariate stats on using the manova function (I included the data set). Now it comes time for a table of effect sizes with significance. The univariate tests are easy. Where I run into trouble filling in the table of effect sizes is the Mahalanobis D as an effect size. I've included the table so you can see what group's I'm comparing. I know there's a great function for filling in ?1 and ?2 : mahalanobis(x, center, cov, inverted=FALSE, ...) I need to turn the sub groups scores for y (young), m (middle) and o (old) into clusters.

The problem is I lack the knowledge around cluster analysis of what goes into the function for [x, center, & cov.] I have only a basic understanding of this topic (a picture of a measured distance between two clusters on a graph). I think I have to turn the data into a matrix but lack direction. Could someone please use my data set or a similar one (a multivariate with at least 3 outcome variables) and actually run this function (mahalanobis). Then please send me your output from [R] starting from the data set all the way to the statistic. PS I know the Mahalanobis D should be ?1=3.93 & ?2=3.04.  

Iíve read and reread the manual around mahalanobis() and have searched through the list serve for information. The info is for people who already have a grasp of how to implement this concept.  

I am running the latest version of R on a windows 7 machine.  

Effect Sizes                                                         
Contrasts|                   Dependent Variables
              Friends              Parents            Strangers        All           
Young-Middle  -1.8768797*         -3.2842941*         -1.1094004*      ?1            
Middle-Old    1.34900725*         1.54919532*         -2.0107882*      ?2           
 
(sorry the column names and values donít line up)
Age      Friend Agression         Parent Agression         Stranger Agression
y          8          7          8
y          5          6          8
y          6          3          7
y          5          5          7
m         15        13        10
m         13        11        9
m         12        12        9
m         18        10        7
o          11        11        10
o          10        4          12
o          12        9          12
o          9          8          14
y          13        7          7
y          9          5          10
y          11        4          4
y          15        3          4
m         14        12        8
m         10        15        11
m         12        11        8
m         10        9          9
o          10        8          11
o          13        11        13
o          9          8          12
o          7          9          16 		 	   		  
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