1) Create a table with two columns: payor and payor.group.
2) Merge that table with your original data
Hadley
On Mon, Jun 28, 2010 at 10:46 AM, GL <pfl...@shands.ufl.edu> wrote:
>
> I'm guessing there's a more efficient way to do the following using the index
> features of R. Appreciate any thoughts....
>
> for (i in 1:nrow(dbs1)){
> if(dbs1$Payor[i] %in% Payor.Group.Medicaid) dbs1$Payor.Group[i] =
> "Medicaid"
> if(dbs1$Payor[i] %in% Payor.Group.Medicare) dbs1$Payor.Group[i] =
> "Medicare"
> if(dbs1$Payor[i] %in% Payor.Group.Commercial) dbs1$Payor.Group[i] =
> "Commercial"
> if(dbs1$Payor[i] %in% Payor.Group.Workers.Comp) dbs1$Payor.Group[i] =
> "Workers Comp"
> if(dbs1$Payor[i] %in% Payor.Group.Self.Pay) dbs1$Payor.Group[i] = "Self
> Pay"
> if(dbs1$Adm.Source[i] %in% Adm.Source.Group.Newborn)
> dbs1$Adm.Source.Group[i] = "Newborn"
> if(dbs1$Adm.Source[i] %in% Adm.Source.Group.ED) dbs1$Adm.Source.Group[i]
> = "ED"
> if(dbs1$Adm.Source[i] %in% Adm.Source.Group.Routine)
> dbs1$Adm.Source.Group[i] = "Routine"
> if(dbs1$Adm.Source[i] %in% Adm.Source.Group.Transfer)
> dbs1$Adm.Source.Group[i] = "Transfer"
> }
> --
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>
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--
Assistant Professor / Dobelman Family Junior Chair
Department of Statistics / Rice University
http://had.co.nz/
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