Hi All,
I'm working with a cross-sectional dataset that has individual respondents (person_id) clustered into groups (group_id). I am trying to demonstrate that variation within groups on a variable of interest is significant, i.e. that individual respondents have different positions within groups, either visually or with tests or both. The variable of interest (ordinal_var) is ordinal and it goes from 1 to 5. The number of groups is large (150).
All techniques I could find work with continuous variables or with longitudinal data.
The dataset looks like this:
I would really appreciate your help on this. Many thanks!
I'm working with a cross-sectional dataset that has individual respondents (person_id) clustered into groups (group_id). I am trying to demonstrate that variation within groups on a variable of interest is significant, i.e. that individual respondents have different positions within groups, either visually or with tests or both. The variable of interest (ordinal_var) is ordinal and it goes from 1 to 5. The number of groups is large (150).
All techniques I could find work with continuous variables or with longitudinal data.
The dataset looks like this:
Code:
* Example generated by -dataex-. For more info, type help dataex clear input byte(person_id group_id ordinal_var) 1 1 2 2 1 2 3 1 3 4 1 1 5 2 4 6 2 2 7 2 1 8 2 3 9 2 5 10 3 5 11 3 4 12 3 2 13 3 1 14 3 3 15 4 1 16 4 1 17 4 2 18 4 2 19 5 3 20 5 4 end