What Comparison-wise type i error is
Comparison-wise type I error is a type of error that occurs when multiple comparisons are made between two or more groups of data. It occurs when a false positive result is accepted as true when in reality, no difference exists between the groups.
Steps for Comparison-wise type I error:
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Define the null hypothesis: This is the hypothesis that the difference between the groups is not statistically significant.
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Define the alternative hypothesis: This is the hypothesis that the difference between the groups is statistically significant.
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Calculate the test statistic and determine the p-value: This is the probability that the difference between the groups is not statistically significant.
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Make a decision: If the p-value is less than the predetermined alpha level (usually 0.05), then reject the null hypothesis and accept the alternative hypothesis. If the p-value is greater than the predetermined alpha level, then accept the null hypothesis and reject the alternative hypothesis.
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Determine if the comparison-wise type I error has been made: If the null hypothesis was accepted, but the groups are actually different, then a comparison-wise type I error has been made.
Examples
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An experimenter sets the significance level of an independent-samples t-test to be 0.05, but the actual p-value of the test turns out to be 0.04. This would be an example of a comparison-wise type I error.
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A researcher performs a chi-squared test and sets the significance level to 0.01, but the calculated p-value is 0.009. This would be an example of a comparison-wise type I error.