SAS 9.4 Proc Calis Method=mlsb available?

[Kpianist]

Hi everyone, I am trying to conduct a confirmatory factor analysis of a 7-factor structure (identified through exploratory factor analysis) consisting of 39 items that were measured on a 5-point likert scale. Since my 39 variables are ordinal, it does not meet the multivariate normality assumption. Therefore, I am attempting to use the robust maximum likelihood using the method=mlsb using proc calis. Is this possible with SAS 9.4? If not, what can I do to use this method with SAS 9.4? 

Thank you in advance! 

[Kpianist]

I meant to write model=MLSB rather than method=MLSB. 🙂

[Kpianist · Accepted solution]

Nevermind. I was right the first time - method=MLSB. I think it's time to sleep! 

[Kpianist]

my code is: 

proc calis data=ifsns_25_3c modification method=mlm; 
factor 
	extendedbf ---> snpre_74 snpre_67 snpre_73 snpre_76 snpre_75 snpre_68 snpre_77 snpre_70, 
	mottocomply ---> snpre_6 snpre_1 snpre_4 snpre_5 snpre_14 snpre_8 snpre_3,
	exbf ---> snpre_38 snpre_45 snpre_44 snpre_43 snpre_39, 
	public ---> snpre_83 snpre_84 snpre_80 snpre_82 snpre_85; 
pvar 
	extendedBF mottocomply exbf public = 4*1.; by fa; 
	run;

and I get the error message: "Assuming the symbol ML was misspelled as mlm." but I meant mlm or mlsb for the Satorra-Bentler method. Can anyone help with this? Thank you! 

[edpsychresearch]

Hi,

I'm trying to run method=mlsb for my CFA, but I'm getting a the following message "You do not provide raw data, which are required by the Satorra-Bentler adjustments of model fit chi-square and standard errors. The estimation method specified is switched to the regular version without the adjustments."  Do you have an example of how you ran the procedure? Here is an example of where I placed the command:

proc calis data=mydata method=mlsb covariance modification;
lineqs
V1 = LV1F1 F1 + E1,
V2 = LV2F1 F1 + E2,
V3 = LV3F2 F2 + E3,
V4 = LV4F2 F2 + E4,
V5 = LV5F3 F3 + E5,
V6 = LV6F3 F3 + E6,
V7 = LV7F4 F4 + E7,
V8 = LV8F4 F4 + E8,
V9 = LV9F5 F5 + E9,
V10 = LV10F5 F5 + E10,
V11 = LV11F5 F5 + E11,
V12 = LV12F6 F6 + E12,
V13 = LV13F6 F6 + E13,
V14 = LV14F7 F7 + E14,
V15 = LV15F7 F7 + E15,
V16 = LV16F8 F8 + E16,
V17 = LV17F8 F8 + E17,
V18 = LV18F9 F9 + E18,
V19 = LV19F9 F9 + E19;
variance
F1 = 1,
F2 = 1,
F3 = 1,
F4 = 1,
F5 = 1,
F6 = 1,
F7 = 1,
F8 = 1,
F9 = 1,
E1-E19 = VARE1-VARE19;
cov
F1 F2 = CF1F2,
F1 F3 = CF1F3,
F1 F4 = CF1F4,
F1 F5 = CF1F5,
F1 F6 = CF1F6,
F1 F7 = CF1F7,
F1 F8 = CF1F8,
F1 F9 = CF1F9,
F2 F3 = CF2F3,
F2 F4 = CF2F4,
F2 F5 = CF2F5,
F2 F6 = CF2F6,
F2 F7 = CF2F7,
F2 F8 = CF2F8,
F2 F9 = CF2F9,
F3 F4 = CF3F4,
F3 F5 = CF3F5,
F4 F5 = CF4F5,
F4 F6 = CF4F6,
F4 F7 = CF4F7,
F6 F7 = CF6F7,
F6 F8 = CF6F8,
F6 F9 = CF6F9,
F7 F8 = CF7F8,
F7 F9 = CF7F9,
F8 F9 = CF8F9;
var V1-V19;
run;