Unformatted text preview: Conditional Probability Bayes' Rule and Screening Tests Symptoms as a Screening Test A symptom or set of symptoms can be used as a screening test. Ideally, we would like to find a set of symptoms such that both PV + and PV  are 1. For a symptom to be effective in predicting disease, it is important that both sensitivity and specificity to be high. Please know, though, that high sensitivity and specificity are not the whole story. Chapter 3: Probability Stat 491: Biostatistics Probability and Inference Definitions and Properties Event Relations Laws of Probability Conditional Probability Bayes' Rule and Screening Tests False Positive and False Negative
When do you think results from a screening test are classified False Positive and when are they classified False Negative. The probability of False positive P(False Positive) = 1  Specificity The probability of False Negative P(False Negative) = 1  Sensitivity Example: Suppose 5% of women with breast cancer have a family history of breast cancer but only 2% women without breast cancer have such a history. Then what is the rate of False Positive and False Negative of family history as a screening test?
Chapter 3: Probability Stat 491: Biostatistics Probability and Inference Definitions and Properties Event Relations Laws of Probability Conditional Probability Bayes' Rule and Screening Tests Example: Association Between PSA and Prostate Cancer
The PSA+ and PSA status of each participant in a study was evaluated and the following data was obtained.
PSA Test Result + + Prostate Cancer + + Frequency 92 27 46 72 Calculate the PV + , PV  , Sensitivity and Specificity. Why is this type of sample is, in general, unrealistic? Typically, casecontrol studies which allow only to estimate sensitivity and specificity but not PV 's are used.
Chapter 3: Probability Stat 491: Biostatistics Probability and Inference Definitions and Properties Event Relations Laws of Probability Conditional Probability Bayes' Rule and Screening Tests Example: Association Between PSA and Prostate Cancer Cont'd... Chapter 3: Probability Stat 491: Biostatistics Probability and Inference Definitions and Properties Event Relations Laws of Probability Condition...
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 Fall '12
 SolomonHarrar
 Statistics, Biostatistics, Conditional Probability, Probability, Probability theory, Type I and type II errors, probability conditional probability, Conditional Probability Bayes, Properties Event Relations

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