Message-ID: <1387827789.21730.YahooMailNeo@web142606.mail.bf1.yahoo.com>
Date: 2013-12-23T19:43:09Z
From: arun
Subject: Calculating group means
In-Reply-To: <94BBEA78-3B6F-43B0-8669-3C7D3D64D74C@aber.ac.uk>
Hi,
You could either try:
#dat1 ##dataset
aggregate(latency~.,data=dat1,mean)
#or
?library(data.table)
?dt1 <- data.table(dat1,key=c('subject','conditionNo','state'))
?dt1[,mean(latency),by=c('subject','conditionNo','state')]
A.K.
On Monday, December 23, 2013 2:20 PM, Laura Bethan Thomas [lbt1] <lbt1 at aber.ac.uk> wrote:
> Hi All,
>
> Sorry for what I imagine is quite a basic question. I have been trying to do is create latency averages for each state (1-8) for each participant (n=13) in each condition (1-10). I'm not sure what function I would need, or what the most efficient ay of calculating this would be. If you have any help with that I would be very grateful.
>
> structure(list(subject = c(1L, 1L, 1L, 1L, 1L, 1L), conditionNo = c(1L,
> 1L, 1L, 1L, 1L, 1L), state = c(5L, 8L, 7L, 8L, 1L, 7L), latency = c(869L,
> 864L, 1004L, 801L, 611L, 679L)), .Names = c("subject", "conditionNo",
> "state", "latency"), row.names = 3:8, class = "data.frame")
>
> Thanks again,
>
> Laura
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