[R] Sensitivity and Specificity

[Prof. Dr. Matthias Kohl]

MKclass::perfMeasures(predict_testing, truth = testing$case, namePos = 1)

should also work and computes 80 performance measures.

Best Matthias

Am 25.10.22 um 06:42 schrieb Jin Li:
> Hi Greg,
> 
> This can be done by:
> spm::pred.acc(testing$case,  predict_testing)
> 
> It will return both sensitivity and specificity, along with a few other
> commonly used measures.
> 
> Hope this helps,
> Jin
> 
> On Tue, Oct 25, 2022 at 6:01 AM Rui Barradas <ruipbarradas using sapo.pt> wrote:
> 
>> Às 16:50 de 24/10/2022, greg holly escreveu:
>>> Hi Michael,
>>>
>>> I appreciate your writing. Here are what I have after;
>>>
>>>> predict_testing <- ifelse(predict > 0.5,1,0)
>>>>
>>>> head(predict)
>>>            1          2          3          5          7          8
>>> 0.29006984 0.28370507 0.10761993 0.02204224 0.12873872 0.08127920
>>>>
>>>> # Sensitivity and Specificity
>>>>
>>>>
>>>
>> sensitivity<-(predict_testing[2,2]/(predict_testing[2,2]+predict_testing[2,1]))*100
>>> Error in predict_testing[2, 2] : incorrect number of dimensions
>>>> sensitivity
>>> function (data, ...)
>>> {
>>>       UseMethod("sensitivity")
>>> }
>>> <bytecode: 0x000002082a2f01d8>
>>> <environment: namespace:caret>
>>>>
>>>>
>>>
>> specificity<-(predict_testing[1,1]/(predict_testing[1,1]+predict_testing[1,2]))*100
>>> Error in predict_testing[1, 1] : incorrect number of dimensions
>>>> specificity
>>> function (data, ...)
>>> {
>>>       UseMethod("specificity")
>>> }
>>> <bytecode: 0x000002082a2fa600>
>>> <environment: namespace:caret>
>>>
>>> On Mon, Oct 24, 2022 at 10:45 AM Michael Dewey <lists using dewey.myzen.co.uk>
>>> wrote:
>>>
>>>> Rather hard to know without seeing what output you expected and what
>>>> error message you got if any but did you mean to summarise your variable
>>>> predict before doing anything with it?
>>>>
>>>> Michael
>>>>
>>>> On 24/10/2022 16:17, greg holly wrote:
>>>>> Hi all R-Help ,
>>>>>
>>>>> After partitioning my data to testing and training (please see below),
>> I
>>>>> need to estimate the Sensitivity and Specificity. I failed. It would be
>>>>> appropriate to get your help.
>>>>>
>>>>> Best regards,
>>>>> Greg
>>>>>
>>>>>
>>>>> inTrain <- createDataPartition(y=data$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]]
>>>
>>> ______________________________________________
>>> 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.
>>
>> Hello,
>>
>> Instead of computing by hand, why not use package caret?
>>
>>
>> tbl <- table(predict_testing, testing$case)
>> caret::sensitivity(tbl)
>> caret::specificity(tbl)
>>
>>
>> Hope this helps,
>>
>> Rui Barradas
>>
>> ______________________________________________
>> 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.
>>
> 
> 

-- 
Prof. Dr. Matthias Kohl
www.stamats.de