coefa_gcm {coefa}

Generate co-occurrence matrices

Description

The co-occurrence matrices are generated by this function. This function can be used obtain the co-occurrence matrix for each primary study.

Usage

coefa_gcm(x, ...)

Arguments

x

A list containing multiple trimmed factor loading matrices

...

Additional parameters which generate the co-occurrence matrices.

Details

The meta-analysts can use this function to obtain the co-occurrence matrix for each primary study. And the algorithm is that a trimmed factor loading matrix multiplies its transpose in the list. As a result, the number of the dimension of the matrix obtained in this step equates with that of the items included in a scale. In this new matrix, the values on the cross-cells indicate the clusters of the items. The greater the value in the cross-cells of a co-occurrence matrix, the bigger the degree of similarity between paired items.

Value

A list containing multiple co-occurrence matrices.

References

Shafer,A. B.(2005). Meta-analysis of the Brief Psychiatric Rating Scale factor structure. Psychological Assessment, 17(3),324–335.

Shafer,A. B. (2006). Meta-analysis of the factor structures of four depression questionnaires: Beck, CES-D, Hamilton, and Zung. Journal of clinical psychology, 62(1), 123–146.

Examples

#Suppose that the matrices.tflm is the factor loading matrices trimmed.
#Note:This is just an example.
#The real co-occurrence matrix should be generated from actual studies.
mx1.tflm<-matrix(c(1,0,0,1,1,0),nrow=2,byrow=2)
mx2.tflm<-matrix(c(1,0,0,1),nrow=2,byrow=2)
matrices.tflm<-list(mx1.tflm,mx2.tflm)
#Generate co-occurrence matrices.
matrices.gcm<-coefa_gcm(matrices.tflm)