Graphics Reference
In-Depth Information
datac$ci
<-
datac$se
*
ciMult
return
return
(datac)
}
The following usage example has a 99% confidence interval and handles
NA
s and missing com-
binations:
# Remove all rows with both c52 and d21
c2
<-
subset(cabbages, !( Cult
==
"c52"
&
Date
==
"d21"
) )
# Set some values to NA
c2$HeadWt[c(
1
,
20
,
45
)]
<-
NNA
summarySE(c2,
"HeadWt"
, c(
"Cult"
,
"Date"
), conf.interval
=
.99
,
na.rm
=
TRUE
TRUE
,
.
drop
=
FALSE
FALSE
)
Cult Date n HeadWt sd se ci
c39 d16
9 3.255556 0.9824855 0.32749517 1.0988731
c39 d20
9 2.722222 0.1394433 0.04648111 0.1559621
c39 d21
10 2.740000 0.9834181 0.31098410 1.0106472
c52 d16
10 2.260000 0.4452215 0.14079141 0.4575489
c52 d20
9 3.044444 0.8094923 0.26983077 0.9053867
c52 d21
0
NaN
NA
NA
NA
Warning message:
In qt(p, df, lower.tail, log.p) : NaNs produced
It will give this warning message when there are missing combinations. This isn't a problem; it
just indicates that it couldn't calculate a quantile for a group with no observations.
See Also
See
Adding Error Bars
to use the values calculated here to add error bars to a graph.
Converting Data from Wide to Long
Problem
You want to convert a data frame from “wide” format to “long” format.
