Getting Started | SAS/STAT 9.1 Users Guide, Volumes 1-7

The TREE procedure creates tree diagrams from a SAS data set containing the tree structure. You can create this type of data set with the CLUSTER or VARCLUS procedure.

In the following example, the VARCLUS procedure is used to divide a set of variables into hierarchical clusters and to create the SAS data set containing the tree structure. The TREE procedure then generates the tree diagrams.

The following data, from Hand, et al. (1994), represent the amount of protein consumed from nine food groups for each of 25 European countries . The nine food groups are red meat ( RedMeat ), white meat ( WhiteMeat ), eggs ( Eggs ), milk ( Milk ), fish ( Fish ), cereal ( Cereal ), starch ( Starch ), nuts ( Nuts ), and fruits and vegetables ( FruVeg ).

The following SAS statements create the data set Protein :

  data Protein;   input Country . RedMeat WhiteMeat Eggs Milk   Fish Cereal Starch Nuts FruVeg;   datalines;   Albania        10.1  1.4  0.5  8.9  0.2  42.3  0.6  5.5  1.7   Austria         8.9 14.0  4.3 19.9  2.1  28.0  3.6  1.3  4.3   Belgium        13.5  9.3  4.1 17.5  4.5  26.6  5.7  2.1  4.0   Bulgaria        7.8  6.0  1.6  8.3  1.2  56.7  1.1  3.7  4.2   Czechoslovakia  9.7 11.4  2.8 12.5  2.0  34.3  5.0  1.1  4.0   Denmark        10.6 10.8  3.7 25.0  9.9  21.9  4.8  0.7  2.4   E Germany       8.4 11.6  3.7 11.1  5.4  24.6  6.5  0.8  3.6   Finland         9.5  4.9  2.7 33.7  5.8  26.3  5.1  1.0  1.4   France         18.0  9.9  3.3 19.5  5.7  28.1  4.8  2.4  6.5   Greece         10.2  3.0  2.8 17.6  5.9  41.7  2.2  7.8  6.5   Hungary         5.3 12.4  2.9  9.7  0.3  40.1  4.0  5.4  4.2   Ireland        13.9 10.0  4.7 25.8  2.2  24.0  6.2  1.6  2.9   Italy           9.0  5.1  2.9 13.7  3.4  36.8  2.1  4.3  6.7   Netherlands     9.5 13.6  3.6 23.4  2.5  22.4  4.2  1.8  3.7   Norway          9.4  4.7  2.7 23.3  9.7  23.0  4.6  1.6  2.7   Poland          6.9 10.2  2.7 19.3  3.0  36.1  5.9  2.0  6.6   Portugal        6.2  3.7  1.1  4.9 14.2  27.0  5.9  4.7  7.9   Romania         6.2  6.3  1.5 11.1  1.0  49.6  3.1  5.3  2.8   Spain           7.1  3.4  3.1  8.6  7.0  29.2  5.7  5.9  7.2   Sweden          9.9  7.8  3.5  4.7  7.5  19.5  3.7  1.4  2.0   Switzerland    13.1 10.1  3.1 23.8  2.3  25.6  2.8  2.4  4.9   UK             17.4  5.7  4.7 20.6  4.3  24.3  4.7  3.4  3.3   USSR            9.3  4.6  2.1 16.6  3.0  43.6  6.4  3.4  2.9   W Germany      11.4 12.5  4.1 18.8  3.4  18.6  5.2  1.5  3.8   Yugoslavia      4.4  5.0  1.2  9.5  0.6  55.9  3.0  5.7  3.2   ;   run;

The data set Protein contains the character variable Country and the nine numeric variables representing the food groups. The $15. in the INPUT statement specifies that the variable Country is a character variable with a length of 15.

The following statements cluster the variables in the data set Protein .The OUTTREE= option creates an output SAS data set named Tree to contain the tree structure. The CENTROID option specifies the centroid clustering method, and the MAXCLUSTERS= option specifies that the largest number of clusters desired is four. The NOPRINT option suppresses the display of the output. The VAR statement specifies that all numeric variables ( RedMeat - FruVeg ) are used by the procedure.

  proc varclus data=Protein outtree=Tree   centroid maxclusters=4 noprint;   var RedMeat--FruVeg;   run;

The output data set Tree , created by the OUTTREE= option in the previous statements, contains the following variables:

_NAME_	the name of the cluster
_PARENT_	the parent of the cluster
_NCL_	the number of clusters
_VAREXP_	the amount of variance explained by the cluster
_PROPOR_	the proportion of variance explained by the clusters at the current level of the tree diagram
_MINPRO_	the minimum proportion of variance explained by a cluster
_MAXEIGEN_	the maximum second eigenvalue of a cluster

The following statements produce a tree diagram of the clusters created by PROC VARCLUS:

  proc tree data=tree ;   proc tree data=tree lineprinter;

PROC TREE is invoked twice. In the first invocation, the tree diagram is presented using the default high resolution graphical output. In the second invocation, the LINEPRINTER option specifies line printer output.

Figure 76.1 displays the default high resolution graphics version of the tree diagram.

Figure 76.1: High Resolution Tree Diagram from PROC TREE

Figure 76.2 displays the same information as Figure 76.1, using line printer output.

  Oblique Centroid Component Clustering   Name of Variable or Cluster   W   h   R     i   e     t                       S     C           F   d     e                       t     e           r   M     M     E     M     F     a     r     N     u   e     e     g     i     i     r     e     u     V   a     a     g     l     s     c     a     t     e   t     t     s     k     h     h     l     s     g   1 +XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX   XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX     XXXXXXXXXXXXX   XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX     XXXXXXXXXXXXX   N  2 +XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX     XXXXXXXXXXXXX   u    XXXXXXXXXXXXXXXXXXX     XXXXXXX     XXXXXXXXXXXXX   m    XXXXXXXXXXXXXXXXXXX     XXXXXXX     XXXXXXXXXXXXX   b  3 +XXXXXXXXXXXXXXXXXXX     XXXXXXX     XXXXXXXXXXXXX   e    XXXXXXXXXXXXXXXXXXX     XXXXXXX     XXXXXXX     .   r    XXXXXXXXXXXXXXXXXXX     XXXXXXX     XXXXXXX     .   4 +XXXXXXXXXXXXXXXXXXX     XXXXXXX     XXXXXXX     .   o    .     .     .     .     .     .     .     .     .   f    .     .     .     .     .     .     .     .     .   5 +.     .     .     .     .     .     .     .     .   C    .     .     .     .     .     .     .     .     .   l    .     .     .     .     .     .     .     .     .   u  6 +.     .     .     .     .     .     .     .     .   s    .     .     .     .     .     .     .     .     .   t    .     .     .     .     .     .     .     .     .   e  7 +.     .     .     .     .     .     .     .     .   r    .     .     .     .     .     .     .     .     .   s    .     .     .     .     .     .     .     .     .   8 +.     .     .     .     .     .     .     .     .   .     .     .     .     .     .     .     .     .   .     .     .     .     .     .     .     .     .   9 +.     .     .     .     .     .     .     .     .

Figure 76.2: Line Printer Graphics Version of the Tree Diagram

In both figures, the name of the cluster is displayed on the horizontal axis and the number of clusters is displayed on the vertical or height axis.

As you look up from the bottom of the figures, clusters are progressively joined until a single, all-encompassing cluster is formed at the top (or root) of the diagram. Clusters exist at each level of the diagram. For example, at the level where the diagram indicates three clusters, the clusters are as follows :

Cluster 1: RedMeat WhiteMeat Eggs Milk
Cluster 2: Fish Starch
Cluster 3: Cereal Nuts FruVeg

As you proceed up the diagram one level, the number of clusters is two. The clusters are

Cluster 1: RedMeat WhiteMeat Eggs Milk Fish Starch
Cluster 2: Cereal Nuts FruVeg

The following statements illustrate how you can specify the numeric variable defining the height of each node (cluster) in the tree. First, the AXIS1 statement is defined. The ORDER= option specifies the data values in the order in which they are to appear on the axis.

Next , the TREE procedure is invoked. The HORIZONTAL option orients the tree diagram horizontally. The HAXIS option specifies that the AXIS1 statement be used to customize the appearance of the horizontal axis. The HEIGHT statement specifies the variable _PROPOR_ (the proportion of variance explained) as the height variable.

  axis1 order=(0 to 1 by 0.2);   proc tree data=Tree horizontal haxis=axis1;   height _PROPOR_;   run;

Figure 76.3 displays the tree diagram oriented horizontally, using the variable _PROPOR_ as the height variable. As you look from left to right in the diagram, objects and clusters are progressively joined until a single, all-encompassing cluster is formed at the right (or root) of the diagram.

Figure 76.3: Horizontal Tree Diagram Using _PROPOR_ as the HEIGHT Variable

Clusters exist at each level of the diagram, represented by horizontal line segments. Each vertical line segment represents a point where leaves and branches are connected into progressively larger clusters.

For example, three clusters are formed at the left-most point along the axis where three horizontal line segments exist. At that point, where a vertical line segment connects the Cereal-Nuts and FruVeg clusters, the proportion of variance explained is about 0.6 ( _PROPOR_ = 0.6). At the next clustering level the variables Fish and Starch are clustered with variables RedMeat through Milk , resulting in a total of two clusters. The proportion of variance explained is about 0.45 at that point.