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The INBREED Procedure

Performing the Analysis

To compute the covariance coefficients for the overlapping generation mode, use the following statements:

   proc inbreed data=Population covar matrix init=0.25;
   run;

Here, the DATA= option names the SAS data set to be analyzed, and the COVAR and MATRIX options tell the procedure to output the covariance coefficients matrix. If you omit the COVAR option, the inbreeding coefficients are output instead of the covariance coefficients.

Note that the PROC INBREED statement also contains the INIT= option. This option gives an initial covariance between any individual and unknown individuals. For example, the covariance between any individual and ‘Jane’ would be 0.25, since ‘Jane’ is unknown, except when ‘Jane’ appears as a parent (see Figure 44.4).

Figure 44.1 Analysis for an Overlapping Population

The INBREED Procedure

Covariance Coefficients
Individual	Parent1	Parent2	George	Lisa	Mark	Scott	Kelly	Amy	Mike	David	Jane	Merle	Jim
George			1.1250	0.2500	0.6875	0.2500	0.2500	0.2500	0.6875	0.4688	0.2500	0.4688	0.4688
Lisa			0.2500	1.1250	0.6875	0.2500	0.6875	0.2500	0.2500	0.6875	0.2500	0.2500	0.6875
Mark	George	Lisa	0.6875	0.6875	1.1250	0.2500	0.5000	0.2500	0.4688	0.8125	0.2500	0.3594	0.8125
Scott			0.2500	0.2500	0.2500	1.1250	0.6875	0.2500	0.2500	0.4688	0.2500	0.2500	0.4688
Kelly	Scott	Lisa	0.2500	0.6875	0.5000	0.6875	1.1250	0.2500	0.2500	0.8125	0.2500	0.2500	0.8125
Amy			0.2500	0.2500	0.2500	0.2500	0.2500	1.1250	0.6875	0.2500	0.2500	0.4688	0.2500
Mike	George	Amy	0.6875	0.2500	0.4688	0.2500	0.2500	0.6875	1.1250	0.3594	0.2500	0.6875	0.3594
David	Mark	Kelly	0.4688	0.6875	0.8125	0.4688	0.8125	0.2500	0.3594	1.2500	0.2500	0.3047	0.8125
Jane			0.2500	0.2500	0.2500	0.2500	0.2500	0.2500	0.2500	0.2500	1.1250	0.6875	0.2500
Merle	Mike	Jane	0.4688	0.2500	0.3594	0.2500	0.2500	0.4688	0.6875	0.3047	0.6875	1.1250	0.3047
Jim	Mark	Kelly	0.4688	0.6875	0.8125	0.4688	0.8125	0.2500	0.3594	0.8125	0.2500	0.3047	1.2500

Number of Individuals	11

In the previous example, PROC INBREED treats the population as a single generation. However, you might want to process the population with respect to distinct, nonoverlapping generations. To accomplish this, you need to identify the generation variable in a CLASS statement, as shown by the following statements:

   proc inbreed data=Population covar matrix init=0.25;
      class Generation;
   run;

Note that, in this case, the covariance matrix is displayed separately for each generation (see Figure 44.5).

You might also want to see covariance coefficient averages within sex categories. This is accomplished by indicating the variable defining the gender of individuals in a GENDER statement and by adding the AVERAGE option to the PROC INBREED statement. For example, the following statements produce the covariance coefficient averages shown in Figure 44.3:

   proc inbreed data=Population covar average init=0.25;
      class Generation;
      gender Sex;
   run;

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