I am trying to run a CFA in R. The code looks like this:
item.model1 <- '
Reflective =~ IES_EFPR_3 + IES_EFPR_10 + IES_EFPR_16 + IES_EFPR_17 + IES_EFPR_23 + IES_EFPR_24 + IES_EFPR_25 + IES_EFPR_26 + IES_RHSC_11 + IES_RHSC_12 + IES_RHSC_13 + IES_RHSC_35 + IES_RHSC_36 + IES_RHSC_37 + IES_BFCC_31 + IES_BFCC_32 + IES_BFCC_33 + SREBQ_A + SREBQ_B + SREBQ_C + SREBQ_D + SREBQ_E
Reactive =~ BES_1 + BES_2 + BES_3 + BES_4 + BES_5 + BES_6 + BES_7 + BES_8 + BES_9 + BES_10 + BES_11 + BES_12 + BES_13 + BES_14 + BES_15 + BES_16 + PFS_1 + PFS_2 + PFS_3 + PFS_4 + PFS_5 + PFS_6 + PFS_7 + PFS_8 + PFS_9 + PFS_10 + PFS_11 + PFS_12 + PFS_13 + PFS_14 + PFS_15 + AEBQ_153 + AEBQ_155 + AEBQ_154 + AEBQ_156 + AEBQ_157 + AEBQ_146 + AEBQ_145 + AEBQ_144 + AEBQ_147 + AEBQ_148 + AEBQ_149 + AEBQ_150 + AEBQ_151 + AEBQ_152 + DEBQ_11 + DEBQ_12 + DEBQ_13 + DEBQ_14 + DEBQ_15 + DEBQ_16 + DEBQ_17 + DEBQ_18 + DEBQ_19 + DEBQ_20 + TFEQ_D_16 + TFEQ_D_25 + TFEQ_D_31 + TFEQ_D_1 + TFEQ_D_2 + TFEQ_D_7 + TFEQ_D_9 + TFEQ_D_11 + TFEQ_D_13 + TFEQ_D_15 + TFEQ_D_20 + TFEQ_D_27 + TFEQ_D_36 + TFEQ_D_45 + TFEQ_D_49 + TFEQ_D_51 + TFEQ_H_3 + TFEQ_H_5 + TFEQ_H_8 + TFEQ_H_12 + TFEQ_H_17 + TFEQ_H_19 + TFEQ_H_22 + TFEQ_H_24 + TFEQ_H_26 + TFEQ_H_29 + TFEQ_H_34 + TFEQ_H_39 + TFEQ_H_41 + TFEQ_H_47 + PNEES_1 + PNEES_2 + PNEES_4 + PNEES_6 + PNEES_7 + PNEES_8 + PNEES_11 + PNEES_12 + PNEES_13 + PNEES_15 + PNEES_16 + PNEES_18
IES.EFPR =~ IES_EFPR_3 + IES_EFPR_10 + IES_EFPR_16 + IES_EFPR_17 + IES_EFPR_23 + IES_EFPR_24 + IES_EFPR_25 + IES_EFPR_26
IES.RHSC =~ IES_RHSC_11 + IES_RHSC_12 + IES_RHSC_13 + IES_RHSC_35 + IES_RHSC_36 + IES_RHSC_37
IES.BFCC =~ IES_BFCC_31 + IES_BFCC_32 + IES_BFCC_33
SREBQ. =~ SREBQ_A + SREBQ_B + SREBQ_C + SREBQ_D + SREBQ_E
BES. =~ BES_1 + BES_2 + BES_3 + BES_4 + BES_5 + BES_6 + BES_7 + BES_8 + BES_9 + BES_10 + BES_11 + BES_12 + BES_13 + BES_14 + BES_15 + BES_16
PFS. =~ PFS_1 + PFS_2 + PFS_3 + PFS_4 + PFS_5 + PFS_6 + PFS_7 + PFS_8 + PFS_9 + PFS_10 + PFS_11 + PFS_12 + PFS_13 + PFS_14 + PFS_15
AEBQ.EOE =~ AEBQ_153 + AEBQ_155 + AEBQ_154 + AEBQ_156 + AEBQ_157
AEBQ.H =~ AEBQ_146 + AEBQ_145 + AEBQ_144 + AEBQ_147 + AEBQ_148
AEBQ.FR =~ AEBQ_149 + AEBQ_150 + AEBQ_151 + AEBQ_152
DEBQ.EX =~ DEBQ_11 + DEBQ_12 + DEBQ_13 + DEBQ_14 + DEBQ_15 + DEBQ_16 + DEBQ_17 + DEBQ_18 + DEBQ_19 + DEBQ_20
TFEQ.D =~ TFEQ_D_16 + TFEQ_D_25 + TFEQ_D_31 + TFEQ_D_1 + TFEQ_D_2 + TFEQ_D_7 + TFEQ_D_9 + TFEQ_D_11 + TFEQ_D_13 + TFEQ_D_15 + TFEQ_D_20 + TFEQ_D_27 + TFEQ_D_36 + TFEQ_D_45 + TFEQ_D_49 + TFEQ_D_51
TFEQ.H =~ TFEQ_H_3 + TFEQ_H_5 + TFEQ_H_8 + TFEQ_H_12 + TFEQ_H_17 + TFEQ_H_19 + TFEQ_H_22 + TFEQ_H_24 + TFEQ_H_26 + TFEQ_H_29 + TFEQ_H_34 + TFEQ_H_39 + TFEQ_H_41 + TFEQ_H_47
PNEES.N =~ PNEES_1 + PNEES_2 + PNEES_4 + PNEES_6 + PNEES_7 + PNEES_8 + PNEES_11 + PNEES_12 + PNEES_13 + PNEES_15 + PNEES_16 + PNEES_18
'
### calculate model
item.cfa.1 <- cfa(item.model1, data = item.dat, missing="pairwise", std.lv = TRUE, ordered =ALL)
summary(item.cfa.1, fit.measures=TRUE, standardized=TRUE)
When I run the code I get this error message:
In lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, :
lavaan WARNING:
Could not compute standard errors! The information matrix could
not be inverted. This may be a symptom that the model is not
identified.
I understand this could be because my model is not identified. However, when I check the df's it says there are 7021 df's. I am also not sure how to test my model to see if it under identified. Any advice would be very helpful.