Dear Joachim,
Storing your data in a long format will make this a lot easier.
library(reshape2)
long.data <- melt(dataset, measure.var = c("A", "B", "C", "D", "E"))
library(car)
leveneTest(value ~ variable, data = long.data)
library(plyr)
ddply(long.data, "variable", function(x){ks.test(x$value})
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey
2015-04-14 10:07 GMT+02:00 Joachim Audenaert <
joachim.audena...@pcsierteelt.be>:
> Hello all,
>
> I am writing a script for statistical comparison of means. I'm doing many
> field trials with plants, where we have to compare the efficacy of
> different treatments on, different groups of plants. Therefore I would
> like to automate this script so it can be used for different datasets of
> different experiments (which will have different dimensions). An example
> dataset is given here under, I would like to compare if the data of 5
> columns (A,B,C,D,E) are statistically different from each other, where A,
> B, C, D and A are different treatments of my plants and I have 5
> replications for this experiment
>
> dataset <- structure(list(A = c(62, 55, 57, 103, 59), B = c(36, 24, 61,
> 19, 79), C = c(33, 97, 54, 48, 166), D = c(106, 82, 116, 85, 94), E =
> c(32, 16, 9, 7, 46)), .Names = c("A", "B", "C", "D", "E"), row.names =
> c(NA, 5L), class = "data.frame")
>
> 1) First I would like to do a levene test to check the equality of
> variances of my datasets. Currently I do this as follows:
>
> library("car")
> attach(dataset)
> y <- c(A,B,C,D,E)
> group <- as.factor(c(rep(1, length(A)), rep(2, length(B)),rep(3,
> length(C)), rep(4, length(D)),rep(5, length(E))))
> leveneTest(y, group)
>
> Is there a way to automate this for all types of datasets, so that I can
> use the same script for a datasets with any number of columns of data to
> compare? My above script only works for a dataset with 5 columns to
> compare
>
> 2) For my boxplots I use
>
> boxplot(dataset)
>
> which gives me all the boxplots of each dataset, so this is how I want it
>
> 3) To check normality I currently use the kolmogorov smirnov test as
> follows
>
> ks.test(A,pnorm)
> ks.test(B,pnorm)
> ks.test(C,pnorm)
> ks.test(D,pnorm)
> ks.test(E,pnorm)
>
> Is there a way to replace the A, B, C, ... on the five lines into one line
> of entry so that the kolmogorov smirnov test is done on all columns of my
> dataset at once?
>
> 4) if data is normally distributed and the variances are equal I want to
> do a t-test and do pairwise comparison, currently like this
>
> pairwise.t.test(y,group,p.adjust.method = "none")
>
> if data is not normally distributed or variances are unequal I do a
> pairwise comparison with the wilcoxon test
>
> pairwise.wilcox.test(y,group,p.adjust.method = "none")
>
> But again I would like to make this easier, is there a way to replace the
> y and group in my datalineby something so it works for any size of
> dataset?
>
> 5) Once I have my paiwise comparison results I know which groups are
> statistically different from others, so I can add a and b and c to
> different groups in my graph. Currently I do this on a sheet of paper by
> comparing them one by one. Is there also a way to automate this? So R
> gives me for example something like this
>
> A: a
> B: a
> C: b
> D: ab
> E: c
>
> All help and commentys are welcome. I'm quite new to R and not a
> statistical genious, so if I'm overseeing things or thinking in a wrong
> way please let me know how I can improve my way of working. In short I
> would like to build a script that can compare the means of different
> groups of data and check if they are statistically diiferent
>
> Met vriendelijke groeten - With kind regards,
>
> Joachim Audenaert
> onderzoeker gewasbescherming - crop protection researcher
>
> PCS | proefcentrum voor sierteelt - ornamental plant research
>
> Schaessestraat 18, 9070 Destelbergen, België
> T: +32 (0)9 353 94 71 | F: +32 (0)9 353 94 95
> E: joachim.audena...@pcsierteelt.be | W: www.pcsierteelt.be
>
> Heb je je individuele begeleiding bemesting (CVBB) al aangevraagd? | Het
> PCS op LinkedIn
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>
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