On Dec 9, 2010, at 10:51 AM, Jon Erik Ween wrote:
Thanks David
What I am trying to do is set up a script that assigns z-scores to a
large dataframe (2500x300, but has Age in years and test scores as
columns.) from a published table of age-corrected standard scores on
this cognitive test.
1) The age intervals in the lookup table are given and not my choice.
You may want to skip the intermediate translation to the row and
column labels and just use the results of findInterval:
> findInterval( 16, c(0, 17, 19, 24, 29, 34, 44, 54, 64, 69, 74, 79,
84, 89) )
[1] 1
> findInterval( 90, c(0, 17, 19, 24, 29, 34, 44, 54, 64, 69, 74, 79,
84, 89) )
[1] 14
Those look like appropriate indices for the column argument
2) Sorry I didn't post an example table, it looks something like
this ("Age" is in the first row, standard scores in the first column):
17 19 24 29 34 44 ....
30 2.6 2.6 2.6 2.6 2.6 2.6
29 1.8 1.8 1.8 2.0 2.6 2.6
28 1.0 1.0 1.8 1.8 2.6 2.6
27 0.0 0.5 1.0 1.8 2.6 2.6
26 -.5 0.0 0.0 1.0 1.8 2.6
.
.
.
.
So, if a subject (row) has age==29 and a standard score of 28, the
value should be 1.8, etc.
Looks like a job for two findInterval indices to be used used with
"[ r , c ] ".
--
David.
Thanks
Jon
Soli Deo Gloria
Jon Erik Ween, MD, MS
Scientist, Kunin-Lunenfeld Applied Research Unit
Director, Stroke Clinic, Brain Health Clinic, Baycrest Centre
Assistant Professor, Dept. of Medicine, Div. of Neurology
University of Toronto Faculty of Medicine
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On 2010-12-09, at 10:33 AM, David Winsemius wrote:
On Dec 9, 2010, at 9:34 AM, Jon Erik Ween wrote:
Hi
This is (hopefully) a bit more cogent phrasing of a previous post.
I'm
trying to compute a z-score to rows in a large dataframe based on
values in
another dataframe. Here's the script (that does not work). 2
questons,
1) Anyone know of a more elegant way to calculate the "rounded"
age value
than the nested ifelse's I've used?
2) how to reference the lookup table based on computed indices?
Thanks
Jon
# Define tables
DSTzlook <-
read.table("/Users/jween/Documents/ResearchProjects/ABC/data/
DSTz.txt",
header=TRUE, sep="\t", na.strings="NA", dec=".", strip.white=TRUE)
df<-stroke
# Compute rounded age.
df$Agetmp
<-ifelse(df$Age>=89,89,ifelse(df$Age>=84,84,ifelse(df
$Age>=79,79,ifelse(df$Age>=74,74,ifelse(df$Age>=69,69,ifelse(df
$Age>=64,64,ifelse(df$Age>=54,54,ifelse(df$Age>=44,44,ifelse(df
$Age>=34,34,ifelse(df$Age>=29,29,ifelse(df$Age>=24,24,ifelse(df
$Age>=19,19,17))))))))))))
Ew, painful. If you want categorized ages (since what the above
coding is producing is not "rounded" in any sense of that word as I
understand it, then why not findInterval() as an index into the
ages you wnat to label these case with?
df$Agetmp <- c(17,19,24,29,34,44,54,64,69,74,79,84)[ # note
Extract operation
findInterval(runif(100,0,100),
c(17,19,24,29,34,44,54,64,69,74,79,84,110) )
] # close extraction
The other option, of course, and a more "honest" one in this
instance would be
cut(vec, breaks=c(...), labels=c(...) )
(It's not clear why you are not picking midpoint ages within those
brackets to me.)
# Reference the lookup table based on computed indices
df$DSTz
<-DSTzlook[which(DSTzlook[,1]==df$Agetmp),which(DSTzlook[1,]==df
$DSF+df$DSB)]
I have not been able to figure out what you are trying to do here.
Trying to use a 2d lookup looks promising a a way to emulate what
an Excel user might attempt, but an example (as requested in the
message at the bottom of every posting) would really be of great
help in making this more concrete for those of us with insufficient
abstractive abilities.
--
David.
# Cleanup
#rm(df)
#df$Agetmp<-NULL
--
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Sent from the R help mailing list archive at Nabble.com.
David Winsemius, MD
West Hartford, CT
David Winsemius, MD
West Hartford, CT
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