PURPOSE Combines a number of different relations or cognitive "slices" of the same network into a single pooled network. These may either be a number of views of the whole network or the view of the whole network through all ego centered networks.
DESCRIPTION The input is a set of k adjacency matrices, each of the form A(i,j) stacked into a three-dimensional matrix, A(i,j,k). This form is useful for cognitive social structures, where k refers to the perceiver of a relation from i to j. This routine compresses this 3-D matrix into a two-dimensional matrix, A'(i,j) using one of two methods. One is to compute the element-wise sum over the k matrices: A'(i,j) = SUM over k of A(i,j,k) This matrix can be dichotomized around a threshold to produce a "consensus" structure.
Alternatively, one can produce a "locally aggregated structure" (LAS) by setting A'(i,j) = A(i,j,i)+A(i,j,j). In other words, the value of a given cell in the aggregate matrix is a function only of the perceptions of the two individuals involved, not the whole group. This matrix can also be dichotomized.
Name of file containing any set of matrices representing the same network. Data type: Valued graph. Multirelational.
Method of Pooling graphs (Default = Slice)
Slice. Take an individuals view of the network. This simply extracts a single matrix from the structure.
Row LAS. Construct a matrix which uses each respondents row as a row in the data matrix. The result is that each row of the data corresponds to the respondents perception of that row.
Column LAS. Construct a matrix which uses each respondents column as a column in the data matrix. The result is that each column of the data corresponds to the respondents perception of that column.
Intersection LAS. Construct a matrix with a connection between i and j if both i and j agree that such a connection exists.
Union LAS. Construct a matrix with a connection between i and j if either i or j state that such a connection exists.
Median LAS. Construct a matrix with values A(i,j) which are the median of i's value of the i,j connection and j's value of the connection.
Consensus. The consensus takes the sum of all the respondents and then dichotomizes the sum.
Average. The average of all the respondents view of the network.
If the users choose either Slice or Consensus then the following parameters will be highlighted.
(For Slice Method) Which informants slice? (Default = 1)
Number of actor to be the informant
(For consensus method) Threshold value (Default =0.5)
Threshold value for dichotomizing the aggregated matrix.
Output dataset (Default = 'Pooled')
Output file that will contain pooled graph .
LOG FILE Pooled graph adjacency matrix.
REFERENCES Krackhardt D. (1987). 'Cognitive social structures'. Social Networks 9, 104-134.