On Dec 13, 2008, at 2:15 PM, js.augus...@gmail.com wrote:
> Does not this give you what you need?
> model.tables(rawfixtimedata.aov,"means", se=TRUE)
I tried that, but get an error:
SEs for type 'means' are not yet implemented
I don't get that error. Using the example and this call
model.tables(npk.aov,"means", se=TRUE)
....I get tables and then:
Standard errors for differences of means
block N P K N:P N:K P:K
2.779 1.604 1.604 1.604 2.269 2.269 2.269
replic. 4 12 12 12 6 6 6
Is your version of R current?
Maybe I'm not using the correct terminology to describe what I need
to do. Using the main effect of Marking as an example, I have the
following mean fixation times for each of 12 subjects:
> txt <-"Sub Absent Present
+ 1 1278 586
+ 2 2410 571
+ 3 408 477
+ 4 645 371
+ 5 265 415
+ 6 4871 354
+ 7 1878 790
+ 8 6064 592
+ 9 761 363
+ 10 1073 566
+ 11 1043 383
+ 12 1170 290"
> marking.t <- read.table(textConnection(txt), header=TRUE,
row.names="Sub")
> marking.t
Absent Present
1 1278 586
2 2410 571
3 408 477
4 645 371
5 265 415
6 4871 354
7 1878 790
8 6064 592
9 761 363
10 1073 566
11 1043 383
12 1170 290
That list copied into R produces this pair of means
> mean(marking.t)
Absent Present
1822.1667 479.8333
The means for markings present and absent, respectively, as reported
by both R and SPSS were:
factor(marking)
Present Absent
480 1822
The standard errors for these means, SE(x) = SD(x)/sqrt(n), should be:
Present Absent
41.42 525.55
> sd(marking.t)/sqrt(nrow(marking.t))
Absent Present
525.58353 41.44599
Which is what SPSS gives. I need to know how to get R to compute the
same values.
Any suggestions?
Thanks,
Jason
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