What Multiple testing is
Multiple testing, also known as multiple hypothesis testing or multiple comparisons, is the process of performing multiple statistical tests on a single dataset in order to draw conclusions about the data. This is generally done when there is a large number of hypotheses to be tested and the data is complex.
The steps for multiple testing are as follows:
- Define the research question or hypothesis
- Identify the variables to be studied
- Determine the number of tests to be performed
- Select the appropriate statistical test(s)
- Calculate the individual test statistics
- Adjust the individual test statistics for multiple comparisons
- Interpret the results of the multiple tests
Examples
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Multiple testing is a statistical technique used to analyze data from multiple experiments to determine which results are significant. It is commonly used in drug research to determine which drugs produce the desired effects.
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Multiple testing is also used in marketing research to identify which variables have the most influence on consumer purchasing decisions.
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Multiple testing is often used in medical research to identify which treatments are the most effective for a particular condition.
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In genetics, multiple testing is used to identify which genes are associated with a particular trait.