
Hi Ritesh,

 what i understad of ROC analysis will be coming in other mail :) 
excellent introduction can be found at 
http://www.csee.usf.edu/~candamo/site/papers/ROCintro.pdf

http://rocr.bioinf.mpi-sb.mpg.de/

take this zip file :)
http://rocr.bioinf.mpi-sb.mpg.de/ROCR_1.0-2.zip
also ROCR and analogue R manual :) they are having good examples :)

please read it in english with the papers given above then it would be 
really easy to interpret ROC curve.
Just try to grasp a simple thing that what is on x axis and what is on y 
axis, further whether the values are in ascending or descending order.
accordingly try to visualize how the ROC space has be analogly divided to 
give digital classification :)

########code starts here and taken from manual of 
nanalogue####################
library(analogue)

## continue the example from roc()
example(roc)

## draw the ROC curve
plot(swap.roc, 1)

## draw the four default diagnostic plots
opar <- par(mfrow = c(2,2))
plot(swap.roc)
par(opar)


#################end of code snippet###########################



############R software working session##################

> 
> ## draw the ROC curve
> plot(swap.roc, 1)
> 
> ## draw the four default diagnostic plots
> opar <- par(mfrow = c(2,2))
> plot(swap.roc)
> par(opar)
> ## continue the example from roc()
> example(roc)

roc> ## continue the example from join()
roc> example(join)

join> ## load the example data
join> data(swapdiat)

join> data(swappH)

join> data(rlgh)

join> ## process so common set of columns for training and test
join> ## number of training set samples
join> n.train <- nrow(swapdiat)

join> ## merge training and test set on columns
join> dat <- join(swapdiat, rlgh, verbose = TRUE)

Summary:

            Rows Cols
Data set 1:  167  277
Data set 2:  101  139
Merged:      268  277


join> ## convert to proportions
join> dat <- dat / 100

join> ## subset data back into training and test sets
join> swapdiat <- dat[1:n.train, ]

join> rlgh <- dat[(n.train+1):nrow(dat), ]

roc> ## fit the MAT model using the squared chord distance measure
roc> swap.mat <- mat(swapdiat, swappH, method = "SQchord")

roc> ## fit the ROC curve to the SWAP diatom data using the MAT results
roc> ## Generate a grouping for the SWAP lakes
roc> clust <- hclust(as.dist(swap.mat$Dij), method = "ward")

roc> grps <- cutree(clust, 12)

roc> ## fit the ROC curve
roc> swap.roc <- roc(swap.mat, groups = grps)

roc> swap.roc

        ROC curve of dissimilarities

Optimal Dissimilarity = 0.894 

AUC = 0.889, p-value: < 2.22e-16
No. within: 1214   No. outside: 12647 

> 
> ## draw the ROC curve
> plot(swap.roc, 1)
> 
> ## draw the four default diagnostic plots
> opar <- par(mfrow = c(2,2))
> plot(swap.roc)
> par(opar)
> 


##############end of demonstration session#########################



Sorry Gaurav,
 
I’ll make sure I mark a copy to r-help also.
 
As I have told, I’m new to R and even to statistics, so it will take some 
time for me to learn it.
 
Just help me get a simple ROC curve, please give an example of your own 
and explain the steps, no mater if its biology or any other field, I just 
need to get the logic behind it.
 
Thanks & Regards
Rithesh M Mohan
 
 

From: gyadav@ccilindia.co.in [mailto:gyadav@ccilindia.co.in] 
Sent: Monday, July 30, 2007 4:28 PM
To: Rithesh M. Mohan
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] ROC curve in R
 

Hi Ritesh 
***please note Ritesh always mark a copy to the R-help mailing list :) *** 


Please visit this link to get help in R 
http://rocr.bioinf.mpi-sb.mpg.de/ROCR_Talk_Tobias_Sing.ppt#384,8,Examples 
(2/8): Precision/recall curves 

futher :) what do you mean by PSA and cohort :) after some googling i got 
this 

co·hort(khôrt) 
n. 
1. A group or band of people. 
2. A companion or associate. 
3. A generational group as defined in demographics, statistics, or market 
research: "The cohort of people aged 30 to 39 . . . were more 
conservative" American Demographics. 
4. 
a. One of the 10 divisions of a Roman legion, consisting of 300 to 600 
men. 
b. A group of soldiers. 

and for PSA i got  Prostate-specific antigen. A substance produced by the 
prostate that may be found in an increased amount in the blood of men who 
have prostate cancer, benign prostatic hyperplasia, or infection or 
inflammation of the prostate. 

Now please clarify what you want to model :) please dont take it otherwise 
i am not from biology field. Please clarify :) 


Regards,

Gaurav Yadav
+++++++++++
Assistant Manager, CCIL, Mumbai (India)
Mob: +919821286118 Email: emailtogauravyadav@gmail.com
Bhagavad Gita:  Man is made by his Belief, as He believes, so He is 


"Rithesh M. Mohan" <rithesh.m@brickworkindia.com> 
07/30/2007 01:30 PM 


To
<gyadav@ccilindia.co.in> 
cc
 
Subject
Re: [R] ROC curve in R
 


 
 




Hi Gaurav, 
  
Need your help, I’m relatively new to R or even stats, so can you please 
give me step by step details to get ROC curve in R. 
  
Requirement. 
  
To build ROC curve using only PSA(variable) alone of the original cohort 
against the ROC of the Model of the original cohort. 
  


It would be really great if you could help me with this. 


  
Thanks and Regards 
Rithesh 

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