[R] Coagulation data by Box/Hunter/Hunter
Kjetil Brinchmann Halvorsen
kjetil at acelerate.com
Fri Aug 20 18:33:55 CEST 2004
The coagulation dataset is from chapter 6 of Box, Hunter&Hunter, and is
used to
introduce comparison of more than two treatments (ANOVA). It is supposedly
coagulation times of blood extracted from animals, after randomizing
the animals
to four groups and giving four different diets.
Some use in R:
coag <- matrix( scan(), 24, 3, byrow=TRUE)
# cutting/pasting from your post into the prompt from scan()
colnames(coag) <- c("time","diet","order")
> coag <- as.data.frame(coag)
> coag$diet <- as.factor(coag$diet)
> oneway.test(time ~ diet, data=coag, var.eq=TRUE)
One-way analysis of means
data: time and diet
F = 13.5714, num df = 3, denom df = 20, p-value = 4.658e-05
with(coag, stripchart(time ~ diet))
Kjetil Halvorsen
T. Murlidharan Nair wrote:
> Hi!!
> Has anyone used the coagulation data for statistical analysis ? I
> managed to
> get the data from the web but unsure of the way its supposed to read.
> I am
> new to R so trying to gets myself familiarized with the statistical
> tools using
> available data. I am appending the data I got of the web. If anyone
> is aware of
> its use I would welcome their input.
> Cheers always!!
> Murli
>
> =======================================================================
> THIS IS DATAPLOT DATA FILE BOXBLOOD.DAT
> DIET EFFECT ON BLOOD COAGULATION
> BOX, HUNTER & HUNTER (1978)
> STATISTIC FOR EXPERIMENTERS
> WILEY, PAGE 165-197 (MAIN EXAMPLE OF CHAPTER 6)
> COMPLETELY RANDOMIZED DESIGN
> NUMBER OF OBSERVATIONS = 24
> TOTAL NUMBER OF VARIABLES PER LINE IMAGE = 3
> RESPONSE VARIABLE = BLOOD COAGULATION TIME
> FACTOR 1 = DIET (4 LEVELS)
> FACTOR 2 = RUN SEQUENCE
> TO READ THIS FILE INTO DATAPLOT (AND ANALYZE)--
> SKIP 25
> READ BOXBLOOD.DAT Y X1 RUNSEQ
> CHAR X ALL
> PLOT Y X1 X1
> .
> ER; ANOVA Y X1
> .
> PLOT RES X1 X1
> PLOT RES PRED PRED
> PLOT RES RUNSEQ
> NORMAL PROBABILITY PLOT RES
> Y X1 RUNSEQ
> -----------------
> 62 1 20
> 60 1 2
> 63 1 11
> 59 1 10
> 63 2 12
> 67 2 9
> 71 2 15
> 64 2 14
> 65 2 4
> 66 2 8
> 68 3 16
> 66 3 7
> 71 3 1
> 67 3 17
> 68 3 13
> 68 3 21
> 56 4 23
> 62 4 3
> 60 4 6
> 61 4 18
> 63 4 22
> 64 4 19
> 63 4 5
> 59 4 24
>
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