Hello people,
I have a great data of mixed variables: binary variables, quantitative variables and categorical variables, multiple level variables (e.g: how important is your family?: 1: very important, 2: important, 3; not important)
I would like to use lasso to choose the suitable variables for regression. I was advised to standardize all the variables before doing that. However, I am still wondering how should I standardize binary variables or multiple level variables? Is it possible?
Besides, I only know the command: egen float (newvar) = std(var), mean(0) std(1) , to standardize one variable. How could I do this to a large number of variables on STATA?
Could you please kindly suggest me some more options?
Thank you very much!
Related Posts with Do I need to standardize a mixed data before doing lasso?
Multiple imputation with panel dataHello, I want to use a multiple imputation panel dataset (originally in SPSS) in Stata. To do so, I…
Restricted cubic splines with cumulative average methodDear all, I am trying to conduct a restricted cubic spline to assess the potential non-linear associ…
Why do country-state pair fixed effects within gravity framework drastically change coefficients and significance?I am investigating the effects of migration on trade. My dataset contains approximately 130 countrie…
Graphing interaction termsI have fitted a two - level cross-classified logistic models using runmlwin (mcmc). I would like to …
chow test for mixed (growth-curve) modelHi, I have a question about the chow test for comparing coefficients in mixed models. On this Stat…
Subscribe to:
Post Comments (Atom)
0 Response to Do I need to standardize a mixed data before doing lasso?
Post a Comment