Dear All,
I am trying to calculate a wealth index using Principal Component Analysis. The quintiles derived from it are to be used as proxy for household socioeconomic status in a regression later.
I am using household income separately as an explanatory variable--my own reasoning being wealth and income are different ideas and it is also in accordance with the literature I am following.
Now, the variables for the index are all binary except for one ordinal categorical variable.
It is suggested that if only ordinal and nominal categorical data is used, multiple correspondence analysis is the apparent method.
However, I am using survey data, and while the user-written command -pca- accommodates for aweight, the other user-written -mca- does not.
What would be the best approach under these circumstances. Would going forward with -pca- be appropriate?
I am trying to calculate a wealth index using Principal Component Analysis. The quintiles derived from it are to be used as proxy for household socioeconomic status in a regression later.
I am using household income separately as an explanatory variable--my own reasoning being wealth and income are different ideas and it is also in accordance with the literature I am following.
Now, the variables for the index are all binary except for one ordinal categorical variable.
It is suggested that if only ordinal and nominal categorical data is used, multiple correspondence analysis is the apparent method.
However, I am using survey data, and while the user-written command -pca- accommodates for aweight, the other user-written -mca- does not.
What would be the best approach under these circumstances. Would going forward with -pca- be appropriate?
