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Old 11-19-2013
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Stats Small doubt in Epidemiology

Guys right now I am doing Epidemiology from Kaplan and while I was watching kaplan videos and going through notes, I was stuck with these doubts. Please anyone take some time and answer

1) The definition of Sensitivity in Kaplan notes is as follows:

"Sensitivity is the proportion of truly diseased persons in the screened population who are identified as diseased by the screening test". if this is the case then the formula should be True positives/ True positives + False positives right. "Identified as diseased by the screening test" means all the cases that came positive by the test should go under denominator right? The actual definition should be "It is the ability of a test to identify the diseased correctly from the total diseased population right?

2) Same with the definition of Specificity

Proportion of truly nondiseased persons who are identified as nondiseased by the screening test. Here if this is the definition the denominator should be True negatives + False negatives and the formula should be True negatives/ True negatives + False negatives. "who are identified as nondiseased by the screening test means True negatives + False negatives right?

3)
Probability of test coming positive given that the patient having the disease is Sensitivity.

Probability of test coming negative given that patient not having the disease is specificity

Probability of patient having the disease if the test comes +ve is Positive predictive value

Probability of patient not having the disease if the test comes -ve is Negative predictive value

Probability of the test coming -ve given that the patient having the disease is False Negative Rate = 1 - sensitivity = False Negatives/ False negatives + True Positives (Total Diseased)

Probability of test coming +ve given that the patient not having the disease is False Positive Rate = 1 - Specificity = False Positives/ False Positives + True Negatives (Total Healthy)

I can decipher this far. Please correct me if I am wrong in any of the above statements

My question here is

What is the formula for "Probability of patient having the disease if the test comes negative" ? Can we do this simply by subtracting Negative predictive value from 1.

What is the formula for "Probability of patient not having the disease if the test comes positive"? Can we do this by subtracting Positive predictive value from 1?

Please guys tell me How to calculate the above two.

Thanx
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Old 11-19-2013
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Quote:
1) The definition of Sensitivity in Kaplan notes is as follows:

"Sensitivity is the proportion of truly diseased persons in the screened population who are identified as diseased by the screening test". if this is the case then the formula should be True positives/ True positives + False positives right. "Identified as diseased by the screening test" means all the cases that came positive by the test should go under denominator right? The actual definition should be "It is the ability of a test to identify the diseased correctly from the total diseased population right?
The definition in Kaplan is correct, though the sentence construction is a bit unclear to understand easily. What they mean is: "Sensitivity is the proportion of truly diseased persons (true positive + false negative) in the screened population WHO ARE IDENTIFIED AS diseased by the screening test (true positive persons)". Replace the word "proportion" with "part of" to understand clearly, they will hold the same meaning. So numerator will be TP and denominator will be TP+FN. Your definition is also correct and means the same thing.

Quote:
2) Same with the definition of Specificity

Proportion of truly nondiseased persons who are identified as nondiseased by the screening test. Here if this is the definition the denominator should be True negatives + False negatives and the formula should be True negatives/ True negatives + False negatives. "who are identified as nondiseased by the screening test means True negatives + False negatives right?
Understand this in the same way: "truly non diseased persons" (true negative + false positive) is the denominator and "identified as nondiseased by the screening test" (true negative) will be the numerator. (They did not write "proportion of A in B", they have instead written "proportion of A who are B".) Read it this way and u will get it.

Quote:
3)
Probability of test coming positive given that the patient having the disease is Sensitivity.

Probability of test coming negative given that patient not having the disease is specificity

Probability of patient having the disease if the test comes +ve is Positive predictive value

Probability of patient not having the disease if the test comes -ve is Negative predictive value
Quote:
Probability of the test coming -ve given that the patient having the disease is False Negative Rate = 1 - sensitivity = False Negatives/ False negatives + True Positives (Total Diseased)
No, 1-sensitivity is not equal to FN/FN+TP ..... 1/sensitivity would be equal to that!



Quote:
Probability of test coming +ve given that the patient not having the disease is False Positive Rate = 1 - Specificity = False Positives/ False Positives + True Negatives (Total Healthy)
Same here too

Quote:
I can decipher this far. Please correct me if I am wrong in any of the above statements

My question here is

What is the formula for "Probability of patient having the disease if the test comes negative" ? Can we do this simply by subtracting Negative predictive value from 1.

What is the formula for "Probability of patient not having the disease if the test comes positive"? Can we do this by subtracting Positive predictive value from 1?

Please guys tell me How to calculate the above two.

Thanx
Yes that would be correct.

(I have just expressed my opinion, I may be wrong
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The above post was thanked by:
devareddy (11-19-2013)
  #3  
Old 11-19-2013
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Correction: Sorry i misunderstood the 1-sensitivity and 1-specificity part... please ignore that!!
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