Jiyoung posted on Saturday, June 20, 2009 - 9:34 am
I want to run a structural equation model. The variables in my model were chosen based on theories that previous studies found.
Along with the variables based on theories, I also want to include demographic variables (e.g., gender, race) to control the effect of demographic variables on endogenous variables. I wonder if it is correct that those demographic variables are just added like other exogenous variables based on theories.
For instance, let's say that I want to predict intention to use the Internet (INTENTION).
My exogenous variables based on theories are 1) perceived ease of use (PEU) and 2) relative advantage (RA). Those are latent variables with multiple indicators. I also want to control the effect of gender, race, income, etc.
First, I will run a CFA to examine the validity of PEU and RA. I will also use the following command: genderL by gender; raceAAL by raceAA; race AsianL by raceAsian; raceWhiteL by raceWhite;
After I make sure the model fit of the CFA model is good, I will move onto the SEM model. I will also use the following command.
Intention on peu ra genderL raceAAL raceAsianL raceWhiteL;
I wonder if I am on the right track. If you could clarify my question, I would appreciate it. Thank you.
I want to include SES as a latent variable in a SEM model. The indicators are: education (educ) - 7 level ordinal indicator income (inc) - 6 level ordinal indicator race/ethnicity (race) - nominal indicator with 5 categories (Black, White, Hispanic, Asian, and other) marital status (mar) - nominal indicator with 5 categories (married, living with partner, divorced, widowed, single never married) nativity (bornUS) - born in US=1 not born US=0
1. I know I need to create dummy variables for the two nominal indicators - marital status and race/ethnicity. What I cannot figure out is how to code the dummy variables and then how to include them in the BY statement for the SES factor.
2. When SES is a latent factor, is it appropriate to have the measured indicators "cause" the latent factor? If so, how is the command for this written?
I tried ML and defining raceth and marital as nominal variables but get an error message that I do not have enough memory. WLSMV seems to work best with my model (except for my lack of understanding of how to write the command for dummies for my two nominal variables).
On pp 449-450 in my users manual (version 5, Nov 2007) is a description of how to refer the the levels of a nominal dependent variables in the MODEL command but no description of how to create dummy variables in the DEFINE command.
I tried this in the DEFINE command: white=raceth==1; black=raceth==2; hispanic=raceth==3;
It seems to work. Is this correct?
If not, please help me - I am just a dumb graduate student ready to pull my hair out... Thanks.
DEFINE; white = 0; if (raceth eq 1) then white = 1; black = 0; if (raceth eq 2) then black = 1; etc.
You need k-1 dummies where k is the number of categories of the nominal variable. Whenever you create a variable in DEFINE, you should check to see that you get the results intended by saving the old and new variables and spot checking.