> df <- read.table(textConnection('Experiment_id Treament_type Value
+ 12345 "control" 3
+ 12345 "full treatment" 4
+ 12345 "full treatment" 5
+ 12345 "partial treatment" 4
+ 10000 "control" 1'), header = TRUE)
> df
Experiment_id Treament_type Value
1 12345 control 3
2 12345 full treatment 4
3 12345 full treatment 5
4 12345 partial treatment 4
5 10000 control 1
> tapply(df$Value, df$Treatment_type, mean)
Error in as.vector(x, mode) : invalid 'mode' argument
# Hey, cut me some slack, I speeled treatment correctly
# Try again:
> tapply(df$Value, df$Treament_type, mean)
control full treatment partial treatment
2.0 4.5 4.0
--
David Winsemius
On Apr 2, 2009, at 12:54 PM, haettulegur wrote:
>
> I have a data frame that looks something like...
>
> Column 1 is an experiment_id, Column 2 is the type of treatment
> ("control",
> "full treatment", or "partial treatment"), and Column 3
is a value.
>
> Experiment_id Treament_type Value
> 12345 "control" 3
> 12345 "full treatment" 4
> 12345 "full treatment" 5
> 12345 "partial treatment" 4
> 10000 "control" 1
>
> What I want to do is this:
> For each experiment_id, compute the mean "control" value, the
mean
> "full
> treatment" value, and the mean "partial treatment" value.
> Is there an easy way to do this?
>
> (Also, for each experiment_id, I then want to find
> 1) "mean full treatment value" - "mean control value"
> 2) "mean partial treatment value" - "mean control
value".)
>
> Thanks!
> --
> View this message in context:
http://www.nabble.com/help-with-two-layers-of-factors-tp22851129p22851129.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
David Winsemius, MD
Heritage Laboratories
West Hartford, CT