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  2. Positive and negative predictive values - Wikipedia

    en.wikipedia.org/wiki/Positive_and_negative...

    The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.

  3. False positives and false negatives - Wikipedia

    en.wikipedia.org/wiki/False_positives_and_false...

    The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.

  4. Likelihood ratios in diagnostic testing - Wikipedia

    en.wikipedia.org/wiki/Likelihood_ratios_in...

    Here "T+" or "T−" denote that the result of the test is positive or negative, respectively. Likewise, "D+" or "D−" denote that the disease is present or absent, respectively. So "true positives" are those that test positive (T+) and have the disease (D+), and "false positives" are those that test positive (T+) but do not have the disease (D ...

  5. Pregnancy test - Wikipedia

    en.wikipedia.org/wiki/Pregnancy_test

    The two primary methods are testing for the female pregnancy hormone (human chorionic gonadotropin (hCG)) in blood or urine using a pregnancy test kit, and scanning with ultrasonography. [1] Testing blood for hCG results in the earliest detection of pregnancy. [2] Almost all pregnant women will have a positive urine pregnancy test one week ...

  6. *This* Is The Best Time Of Day To Take A Pregnancy Test For ...

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  7. Pre- and post-test probability - Wikipedia

    en.wikipedia.org/wiki/Pre-_and_post-test_probability

    Diagram relating pre- and post-test probabilities, with the green curve (upper left half) representing a positive test, and the red curve (lower right half) representing a negative test, for the case of 90% sensitivity and 90% specificity, corresponding to a likelihood ratio positive of 9, and a likelihood ratio negative of 0.111.

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