Hi
I have a cross sectional study (individuals from 26 countries) in an RD-design. The treatment is Trump's electoral victory, dependent variable is satisfaction with democracy.
On the individual level, the respondents are as if-randomised. However, some countries are under- or overrepresented in either the control or the treatment group (due to differences in the exact dates when Eurobarometer conducted interviews in the different countries). For instance, Germans constitute 9 % of the control group, but only 3 % of the treatment group. Therefore I want to apply weights to the data. Concretely, treatment-Germans would have to weight 3x as much as control-Germans. The difficulty for me lies in that this weight must be different for every country. I.e. I have one variable (country) where a weight must be applied to EACH value on the variable (e.g. country 1=France, 2=Germany, etc.). Is this possible? Can I do something after creating dummy variables for each nationality?
Thanks!
Related Posts with Balancing treatment and control group with - weight -
Mode/modal regressionHi, I want to run a (linear) mode/modal regression model (something like proposed by Lee (1989), Mod…
invalid 'h' r(198) error in foreach loopDear statalists, I am currently working to extract specific variables from the British Househould P…
Cannot get mm_root to solve an equation for which excel shows there is an answerDear Statalist, I have been trying to solve for r in the function described below. I cannot figure …
How to use putexcel after testparmHi all, I am trying to use the put excel function after testparm, but not sure how to go about it. …
t-tests under heteroskedasticityHi everyone, I am trying to analyse how the variable "score" varies over time. I have used the follo…
Subscribe to:
Post Comments (Atom)
0 Response to Balancing treatment and control group with - weight -
Post a Comment