Good afternoon!

 I have the following data:

a<-data.frame (id_hh=c(1:5), strata=c(1,1,2,2,1), Nhstrata=c(100,100,200,200,100), Nrmemb=c(2,4,2,5,4))
a$ocmemb1<-c("wk","jl","st","jl","st")
 a$ocmemb2<-c("wk","jl","st","wk","wk")

where id_hh is a code of identification for the household (my analysis refers to households), strata is the strata from which the hh is sampled, Nhstrata is the dimension of the population strata from which the hh is sampled, nrmemb is the no of members in a hh and ocmemb1,2...is the occupation of each individual member of the hh (worker,jobless,student).

> a
  id_hh strata Nhstrata Nrmemb ocmemb1 ocmemb2
1     1      1      100      2       wk      wk
2     2      1      100      4      jl      jl
3     3      2      200      2      st      st
4     4      2      200      5      jl      wk
5     5      1      100      4      st      wk

Now, is there a possibility of designing some weights for each household based on the characteristics of individuals which form the hh? Say, I want to calibrate each hh for its occupational category but i don't have the additional data for household, rather it is available for individuals, ex: I don't know that 32% of households are included in the category of  studenthh (inclusion which is based on the status of the head of hh), but i know that 32% of all the individuals from which the sample of hhs is drawn are all students. So, is there a possibility of designing these weights for hhs where additional information is available for the individuals which form that hhs? And is it a solid way of calibrating, i mean is it reliable and trustworthy? Could the survey package do it?


Thank you and have a great day!

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