Does anyone successfully run Bartlett and KMO with the computed covariance matrix resulted from mifa? These are two important tests to check before going into EFA. I can run FA with dat$cov_combined, but not Bartlett or KMO. I would really appreciate it if there's any thoughts or advice!
dat_bart <- cortest.bartlett(dat$cov_combined, n = 426, diag = TRUE)
Warning message:
In log(detR) : NaNs produced
KMO(dat$cov_combined)
Error in solve.default(r) :
system is computationally singular: reciprocal condition number = 6.46123e-19
matrix is not invertible, image not found
Does anyone successfully run Bartlett and KMO with the computed covariance matrix resulted from mifa? These are two important tests to check before going into EFA. I can run FA with dat$cov_combined, but not Bartlett or KMO. I would really appreciate it if there's any thoughts or advice!
dat_bart <- cortest.bartlett(dat$cov_combined, n = 426, diag = TRUE)
Warning message:
In log(detR) : NaNs produced
KMO(dat$cov_combined)
Error in solve.default(r) :
system is computationally singular: reciprocal condition number = 6.46123e-19
matrix is not invertible, image not found