Hello guys, I created an example data set:
structure(list(pa = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), a1 = c(84,
108, 113, 99, 98, 88, 90, 89, 95, 77), a2 = c(113, 101, 99, 108,
122, 92, 90, 110, 109, 95), a3 = c(96, 108, 110, 99, 118, 100,
90, 89, 102, 99), a4 = c(76, 106, 94, 124, 91, 103, 107, 106,
113, 96)), .Names = c(pa, a1, a2, a3, a4), row.names = c(NA,
-10L), class = data.frame)
So the data frame contains the numbers of my participants (1 to 10) and the
score, they hit on 4 tasks (a1 to a4).
I wrote this function, to use on the data:
pe-apply(X=my.data[,c(a1,a2,a3,a4)],
MARGIN=2,
FUN=quantile,
probs=seq(0,1,by=.01),
na.rm=TRUE)
round(pe,0)
It computes the percentiles of each task. So when using this function I know,
that e.g.
a person who got 77 points on task 1 (a1) has a percentile of 0%.
If a person scores 88 points then he/she got the percentiles 21% to 27%, so 27%
got the same amount of points or less.
In comparison in task 4 (a4) a person reaching 77 points has a percentile of 1%.
Now I want to add 4 columns to my.data (pe1 to pe4).
The final data frame my.data shall have 10 rows and 9 columns
These columns (pe1 to pe4) shall show the maximum percentile someone reached
according to his points for each task.
So for the person who reached 77 points in a1 the respective pe1 would be 0.
For all the people who reached 88 points in a1 the respective pe1 would be 27.
For all the people who reached 77 points in a4 the respective pe1 would be 1.
The final data frame my.data shall have 10 rows and 9 columns.
So for the first participant (pa=1), the pe's would be a1=84 -- pe=12; a2=113
-- pe=89, a3=96 -- pe=24, a4=76 -- pe=0
I hope, that is clearer than before :)
Thanks a lot,
Anne
Am 24.07.2013 14:47, schrieb John Kane:
Welcome to R-help
it is a bit hard to see exactly what you want without data. Rest of the
explanation looks good though it appears you may have sent this in HTML and
the list asks for text. It strips out the html and we lose any html format.
Can I suggest reading these
https://github.com/hadley/devtools/wiki/Reproducibility
http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
and then getting back to use with some data. The best way to provide data ,
as is described in the above links is to use dput() (type ?dput for help )
and then just copy and paste the results into the mail.
John Kane
Kingston ON Canada
-Original Message-
From: gallr...@psychologie.tu-dresden.de
Sent: Wed, 24 Jul 2013 12:25:35 +0200
To: r-help@r-project.org
Subject: [R] Function, that assigns two vectors to each other
Hey guys,
In my data setv (KD) I have 4 columns
(Punkte.AG1,Punkte.AG2,Punkte.AG3,Punkte.WI) I'm interested in.
These columns contain the participants' scores of a specific task.
I computed the percentiles of the columns using this code:
pe-apply(X=KD[,c(Punkte.AG1,Punkte.AG2,Punkte.AG3,Punkte.WI)],
MARGIN=2,
FUN=quantile,
probs=seq(0,1,by=.01),
na.rm=TRUE)
round(pe,0)
This is the output (to the 20^th percentile):
pe
Punkte.AG1 Punkte.AG2 Punkte.AG3 Punkte.WI
0%6319
1%74311
2%86312
3%87412
4%97512
5%98512
6%108512
7%108512
8%108614
9%109614
10%109615
11%1010715
12%1010715
13%1110715
14%1110816
15%1110816
16%1110816
17%1110816
18%1110816
19%1210816
20%1210816
So now I know, what percentile a person has, when she/ he scored a
certain amount of points (e.g. 6 points in Punkte.AG1 = 0%).
Here is my problem:
I now want to write a function that assigns the percentile to the score
(for each task) and saves it in a new variable.
So every person that scored 10 in Punkte.AG1 gets a 12 in the new
variable Percentile.AG1.
Every person that scored 6 in Punkte.AG1 gets a 6 in the new
variable Percentile.AG1.
The same thing should be done for the other tasks.
I new to R, so I don't have any clue, how to solve that. It would be
awesome, if you would know how to handle that.
Thanks a lot!
Anne
--
M. Sc. Anne-Marie B. Gallrein
Technische Universitdt Dresden
Institut f|r Klinische, Diagnostische und Differentielle Psychologie
Diagnostik und Intervention
01062 Dresden
Tel. +49 351 463-34004
gallr...@psychologie.tu-dresden.de
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