coefa: A R Package for Meta Analysis of Factor Analysis Based on Co-occurrence Matrices
1 Introduction | 2 The coefa R package | 2.1 Five steps of COEFA in coefa package | Step1: Obtain factor loading matrices for the EFA in the original study | Step2: Assign (Trim) the original factor loading matrices. Significant loading in factor loading matrices (loading greater than cutoff ) are assigned a value of 1, and the others are assigned a value of 0. | Step3: Generate co-occurrence matrices using each factor loading matrix multiply its transport. | Step4: Aggregate co-occurrence matrix. The users have two options,weight by sample size or not. | Step5: Exploratory factor analysis or principal component analysis using the Aggregated co-occurrence matrix. | 2.2 Environment of the coefa package runing. | 2.3 Usage of coefa package | Step1:Obtain factor loading matrices for the EFA in the original study. | Step2: Assign (Trim) the original factor loading matrices.Significant loading in factor loading matrices (loading greater than the cutoff value ) are assigned a value of 1, and the others are assigned a value of 0. | Step3: Generate the co-occurrence matrices for each primary study. | Step4: Generate the aggregated co-occurrence matrix. | Step5: Exploratory factor analysis or principal component analysis Using the Aggregated co-occurrence matrix. | References
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