I got my article manuscript back from review and one notion from a reviewer was that in my analyses "[s]tandard errors are not corrected for heterogeneity or intra-group correlation", s/he apparently thinks they should. I'm slightly confused about this.
I have used World Values Survey (WVS) data, where unit of observation is one interviewed person. I have analysed respondents from ten countries of the data (I have country as control variable (coded as a set of dummy variables)), togehter there are some 10 000 respondents in my analyses. Based on what WVS states, the data is representative of all people in the age 18 and older residing within private households in each country. The sampling method of the data is (depending on country) full probability or a combination of probability and stratified (see this, for more specific description by country, select one country here and see Sampling & Methodology). Respondents are interviewed separately.
I have used binary logistic regression and OLS regression. My dependent variables are participation in protests and interest in politics and independent variables are such as education, employment status, income, age, gender etc.
Based on what I have found (for example this and asuming that the term "intra-group correlation" is synonym to "intra-class correlation" (as I would understand based for example on how these terms are used here)), in my case intra-group correlation would occur if respondents were taken from certain groups (they were family members for example) and respondents within these groups had tended to answer similarly. However, this is not the case, the observations should be independent. With heterogeneity I'm equally puzzled.
My question is twofold (or actually fourfold): 1) Is heterogeneity and 2) intra-group correlation something I should be worried about when working with WVS? And if so, 3) How to correct for heterogeneity or 4) intra-group correlation using SPSS?
I am thankful for all advice.