I have a set of data that consists of a number of biological measurements.
The columns are Time that runs from 01/01/2005 to 01/5/2007, Group which has
23 levels and postcode which is nested within group. This is a balanced panel
but the number of postcodes differs within groups, from 15 to 400. The rest of
this data consists of a number of columns of quantitative measures, largely
counts.
I would like to set this up as a dataframe but retain the time series element
and the structural relations within the data. How can I do this in R?
Whenever I try ts I end up with things out of order without the time series
element.correctly represented
Secondly assuming that I wish to regress temperature against vegetation and
type how do I express this as a linear hierarchical model nesting postcode
within group but keeping time as non nested (eg group x time) with calendar time
as a group level predictor?
Any help would be most appreciated.
Graham Leask
Kind regards
Dr Graham Leask
Economics and Strategy Group
Aston Business School
Aston University
Aston Triangle
Birmingham
B4 7ET
Tel: Direct line 0121 204 3150
Fax: 0870 759 8408
email g.leask@aston.ac.uk
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