[R] Sensitivity and Specificity

greg holly m@k@hho||y @end|ng |rom gm@||@com
Mon Oct 24 17:50:27 CEST 2022


Hi Michael,

I appreciate your writing. Here are what I have after;

> predict_testing <- ifelse(predict > 0.5,1,0)
>
> head(predict)
         1          2          3          5          7          8
0.29006984 0.28370507 0.10761993 0.02204224 0.12873872 0.08127920
>
> # Sensitivity and Specificity
>
>
sensitivity<-(predict_testing[2,2]/(predict_testing[2,2]+predict_testing[2,1]))*100
Error in predict_testing[2, 2] : incorrect number of dimensions
> sensitivity
function (data, ...)
{
    UseMethod("sensitivity")
}
<bytecode: 0x000002082a2f01d8>
<environment: namespace:caret>
>
>
specificity<-(predict_testing[1,1]/(predict_testing[1,1]+predict_testing[1,2]))*100
Error in predict_testing[1, 1] : incorrect number of dimensions
> specificity
function (data, ...)
{
    UseMethod("specificity")
}
<bytecode: 0x000002082a2fa600>
<environment: namespace:caret>

On Mon, Oct 24, 2022 at 10:45 AM Michael Dewey <lists using dewey.myzen.co.uk>
wrote:

> Rather hard to know without seeing what output you expected and what
> error message you got if any but did you mean to summarise your variable
> predict before doing anything with it?
>
> Michael
>
> On 24/10/2022 16:17, greg holly wrote:
> > Hi all R-Help ,
> >
> > After partitioning my data to testing and training (please see below), I
> > need to estimate the Sensitivity and Specificity. I failed. It would be
> > appropriate to get your help.
> >
> > Best regards,
> > Greg
> >
> >
> > inTrain <- createDataPartition(y=data$case,
> >                                 p=0.7,
> >                                 list=FALSE)
> > training <- data[ inTrain,]
> > testing  <- data[-inTrain,]
> >
> > attach(training)
> > #model training and prediction
> > data_training <- glm(case ~ age+BMI+Calcium+Albumin+meno_1, data =
> > training, family = binomial(link="logit"))
> >
> > predict <- predict(data_training, data_predict = testing, type =
> "response")
> >
> > predict_testing <- ifelse(predict > 0.5,1,0)
> >
> > # Sensitivity and Specificity
> >
> >
>  sensitivity<-(predict_testing[2,2]/(predict_testing[2,2]+predict_testing[2,1]))*100
> >   sensitivity
> >
> >
>  specificity<-(predict_testing[1,1]/(predict_testing[1,1]+predict_testing[1,2]))*100
> >   specificity
> >
> >       [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> --
> Michael
> http://www.dewey.myzen.co.uk/home.html
>

	[[alternative HTML version deleted]]



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