Related variables at different levels
Posted: Wed Oct 31, 2018 10:26 am
Hi all
I have a 2-level model in which individuals (lower level 1) and nested within communities (higher level 2). The outcome measure is binary: whether or not an individual needs to access a particular social service.
One of the level-1 variables I need to include is ethnicity. It is considered very likely for various reasons that an individual's ethnicity will affect the probability that they will access the social service; for example, the impact of a family's ethnicity on the likelihood that they will be suffering economic hardship, be surrounded by (or be lacking) systems of informal support, be willing (or unwilling) to seek/accept help, and so on.
One of my colleagues has also requested that the same ethnicity information is additionally processed into a community (Level 2) variable (e.g. proportion of non-white individuals in the community). His logic is that there could be issues of context - so that the way, say, an Asian family is able to cope with personal/economic difficulties might be very different if they are in a virtually all-white community as opposed to a community with a high proportion of Asian families. Also, among other reasons, the community-level ethnicity profile could serve to proxy some important characteristics of the broader socio-cultural and economic environment of different communities.
I see his arguments, but I am somewhat hesitant about using the same data to create different variables at different levels of the model. I don't think I would generally use two variables derived from the same data in single-level regression model.
Does anyone have an opinion on whether my colleague's request would be valid?
Many thanks in anticipation
John
I have a 2-level model in which individuals (lower level 1) and nested within communities (higher level 2). The outcome measure is binary: whether or not an individual needs to access a particular social service.
One of the level-1 variables I need to include is ethnicity. It is considered very likely for various reasons that an individual's ethnicity will affect the probability that they will access the social service; for example, the impact of a family's ethnicity on the likelihood that they will be suffering economic hardship, be surrounded by (or be lacking) systems of informal support, be willing (or unwilling) to seek/accept help, and so on.
One of my colleagues has also requested that the same ethnicity information is additionally processed into a community (Level 2) variable (e.g. proportion of non-white individuals in the community). His logic is that there could be issues of context - so that the way, say, an Asian family is able to cope with personal/economic difficulties might be very different if they are in a virtually all-white community as opposed to a community with a high proportion of Asian families. Also, among other reasons, the community-level ethnicity profile could serve to proxy some important characteristics of the broader socio-cultural and economic environment of different communities.
I see his arguments, but I am somewhat hesitant about using the same data to create different variables at different levels of the model. I don't think I would generally use two variables derived from the same data in single-level regression model.
Does anyone have an opinion on whether my colleague's request would be valid?
Many thanks in anticipation
John