For rare diseases, people tend to intuitively overestimate the probability of being sick after having received a positive test result. This probability is calculated using Bayes's theorem from some of the conditional probabilities involved in the scenario. Understanding these probabilities, such as the probability of being sick when having received a positive test result, expressed as P(sick| positive test), can become easier using a contingency table like the one shown. Given properties of the test, the probability of the disease, and the size of the reference group, the table shows the number of people falling into the four different possible categories. The conditional probability of being sick after having received a positive test resul...
• Conditional probability provides us with a way to reason about the outcome of an experiment, based...
This paper addresses the nature of the prior prob-abilities of diseases for probabilistic diagnostic...
Is it possible to measure the dispersion of ex ante chances (i.e., chances “before the event”) among...
For rare diseases, people tend to intuitively overestimate the probability of being sick after havin...
Establishing an accurate diagnosis is crucial in everyday clinical practice. It forms the starting p...
This article reintroduces a different form of Bayes' theorem that allows calculation of posttes...
[[abstract]]Sensitivity and specificity describe the accuracy of a test. In a clinical setting, we d...
It is often the case that a clinician has diagnostic values such as sensitivity and specificity avai...
It is common in population screening surveys or in the investigation of new diagnostic tests to have...
<div><p>Ruling out disease often requires expensive or potentially harmful confirmation testing. For...
Most neuropsychologists are aware that, given the specificity and sensitivity of a test and an estim...
RATIONALEBedside use of Bayes' theorem for estimating probabilities of diseases is cumbersome. An al...
Ruling out disease often requires expensive or potentially harmful confirmation testing. For such te...
<p>Relation between prior disease probability, proportion of negative confirmation tests, and propor...
One of the most interesting applications of the results of probability theory involves estimating un...
• Conditional probability provides us with a way to reason about the outcome of an experiment, based...
This paper addresses the nature of the prior prob-abilities of diseases for probabilistic diagnostic...
Is it possible to measure the dispersion of ex ante chances (i.e., chances “before the event”) among...
For rare diseases, people tend to intuitively overestimate the probability of being sick after havin...
Establishing an accurate diagnosis is crucial in everyday clinical practice. It forms the starting p...
This article reintroduces a different form of Bayes' theorem that allows calculation of posttes...
[[abstract]]Sensitivity and specificity describe the accuracy of a test. In a clinical setting, we d...
It is often the case that a clinician has diagnostic values such as sensitivity and specificity avai...
It is common in population screening surveys or in the investigation of new diagnostic tests to have...
<div><p>Ruling out disease often requires expensive or potentially harmful confirmation testing. For...
Most neuropsychologists are aware that, given the specificity and sensitivity of a test and an estim...
RATIONALEBedside use of Bayes' theorem for estimating probabilities of diseases is cumbersome. An al...
Ruling out disease often requires expensive or potentially harmful confirmation testing. For such te...
<p>Relation between prior disease probability, proportion of negative confirmation tests, and propor...
One of the most interesting applications of the results of probability theory involves estimating un...
• Conditional probability provides us with a way to reason about the outcome of an experiment, based...
This paper addresses the nature of the prior prob-abilities of diseases for probabilistic diagnostic...
Is it possible to measure the dispersion of ex ante chances (i.e., chances “before the event”) among...