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
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--
Michael
http://www.dewey.myzen.co.uk/home.html
______________________________________________
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and provide commented, minimal, self-contained, reproducible code.
