Hi,
first of all, you shouldn't backtransform your prediction, use the option
type=response instead :
salichpred<-predict(salic.lr,
newdata=profilevalidation,type="response")
limit <- 0.5
salichpredcat <- ifelse(salichpred<limit,0,1) # prediction of categories.
Read in on sensitivity, specificity and ROC-curves. With changing the limit,
you can calculate sensitivity and specificity, and you can construct a ROC
curve that will tell you how well your predictions are. It all depends on
how much error you allow on the predictions.
Cheers
Joris
On Wed, May 26, 2010 at 10:04 AM, azam jaafari
<azamjaafari@yahoo.com>wrote:
> Hi
>
> I did validation for prediction by logistic regression according to
> following:
>
> validationsize <- 23
> set.seed(1)
> random<-runif(123)
> order(random)
> nrprofilesinsample<-sort(order(random)[1:100])
> profilesample <- data[nrprofilesinsample,]
> profilevalidation <- data[-nrprofilesinsample,]
> salich<-profilesample$SALIC.H.1
> salic.lr<-glm(salich~wetnessindex, profilesample,
> family=binomial('logit'))
> summary(salic.lr)
> salichpred<-predict(salic.lr, newdata=profilevalidation)
> expsalichpred<-exp(salichpred)
> salichprediction<-(expsalichpred/(1+expsalichpred))
>
> So,
> table(salichprediction, profilevalidation$SALIC.H.1)
>
> in result:
> salichprediction 0 1
> 0.0408806327422231 1 0
> 0.094509645033899 1 0
> 0.118665480273383 1 0
> 0.129685441514168 1 0
> 0.13545295569511 1 0
> 0.137580612201769 1 0
> 0.197265822234215 1 0
> 0.199278585548248 0 1
> 0.202436276322278 1 0
> 0.211278767985746 1 0
> 0.261036846823867 1 0
> 0.283792703256058 1 0
> 0.362229486187581 0 1
> 0.362795636267779 1 0
> 0.409067386115694 1 0
> 0.410860613509484 0 1
> 0.423960962956254 1 0
> 0.428164288793652 1 0
> 0.448509687866763 0 1
> 0.538401659478058 0 1
> 0.557282539294224 1 0
> 0.603881788227797 0 1
> 0.63633478460736 0 1
>
> So, I have salichprediction between 0 to 1 and binary variable(observed
> values) 0 or 1. I want to compare these data together and I want to know is
> ok this model(logistic regression) for prediction or no?
>
> please help me?
>
> Thanks alot
>
> Azam
>
>
>
>
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>
>
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>
>
--
Joris Meys
Statistical Consultant
Ghent University
Faculty of Bioscience Engineering
Department of Applied mathematics, biometrics and process control
Coupure Links 653
B-9000 Gent
tel : +32 9 264 59 87
Joris.Meys@Ugent.be
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