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# Statistical Features of Diagnostics

**10 STUDENTS ENROLLED**

**Course Availability: **Unlimited views for 72 hours from time of purchase**
Course Running Time:** 47 min | Assessment: 20 min

**Course Material:**Downloadable PDF of all presented slides

**Preview Now:**Specificity & Sensitivity

**Statistical Features Of Diagnostics** explores the basic measurement concepts used in the development and evaluation of a diagnostic. These included variability and distribution, standard curve, accuracy, and sensitivity and specificity. Using these measurements participants learned how false negative/false positive are determined and how those results are compared to a “Gold Standard” to determine the likelihood of receiving diagnostic approval for marketing. *Running time: 47 minutes/Assessment: 20 minutes*

**Measures: Determining Unknowns**

At the end of this section you should be able to:

1. Identify the gold standard

2. Appreciate how testing a new diagnostics against a gold standard is crucial when seeking FDA approval

2. Produce, use, and interpret a standard curve

**Measures: Variability & Distributions**

At the end of this section you should be able to:

1. Interpret measurements and graphic distributions

2. Determine if a patient falls into normal or abnormal distribution for disease as determined by diagnostic tests

**Examples of Test Distributions**

At the end of this section you should be able to:

1. Analyze various bi-model distributions diagnostic tests to determine if patients fall within the normal or abnormal range for disease

2. Identify an ideal distribution for diagnostic tests

**Measurement Considerations**

At the end of this section you should be able to:

1. Recognize all measurements have sample and instrument variability

2. Choose the correct measurements to determine disease state of a patient

**Accuracy of a Measurement**

At the end of this section you should be able to:

1. Define accuracy, precision, and bias

2. Determine if a diagnostic is accurate or not

**Specificity & Sensitivity**

At the end of this section you should be able to:

1. Differentiate between sensitivity and specificity

2. Calculate and interpret sensitivity and specificity

**Positives & Negatives**

At the end of this section you should be able to:

1. Define false positive and false negative

2. Calculate and interpret percentages of false positives and false negative

**Risks of Diagnostics**

At the end of this section you should be able to:

1. Calculate and interpret positive predictive value

2. Understand how to use a ROC curve and interpret the strength of the diagnostic

**Examples of Diagnostics: Mammogram & PSA Testing**

At the end of this section you should be able to:

1. Explain the risks associated with screening for low prevalence diseases

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