[R] set dataframe field value from lookup table

[Jon Erik Ween]

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.

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.

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

Kimel Family Building, 6th Floor, Room 644 
Baycrest Centre
3560 Bathurst Street 
Toronto, Ontario M6A 2E1
Canada 

Phone: 416-785-2500 x3648
Fax: 416-785-2484
Email: jween at klaru-baycrest.on.ca


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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
>> -- 
>> View this message in context: http://r.789695.n4.nabble.com/set-dataframe-field-value-from-lookup-table-tp3080245p3080245.html
>> Sent from the R help mailing list archive at Nabble.com.
>> 
> 
> 
> David Winsemius, MD
> West Hartford, CT
>