A conservative correction method for inflated "Alpha values" based on multiple comparisons being carried out independently on a specific data set, is known as...?
A. Ad Hoc Testing
B. Tukey's honestly significan differences (HSD)
C. Post Hoc testing
D. Bonferroni correction
D. Bonferroni correction: alters the alpha (alpha error adjustment).
The correct answer is D. Bonferroni correction.
To arrive at this answer, we first need to understand the terms mentioned in the question.
1. "Alpha values" refer to the level of significance used in hypothesis testing. It is the predetermined threshold that determines if a result is statistically significant or not.
2. "Multiple comparisons" means conducting multiple statistical tests or hypothesis tests on the same dataset, which can lead to an increased chance of falsely detecting significant results due to random chance.
Now, let's break down the options and explain why the correct answer is D.
A. Ad Hoc Testing: This refers to a situation when tests are conducted without a specific plan or pre-defined criteria. It doesn't address the issue of inflated alpha values caused by multiple comparisons and is therefore not the correct answer.
B. Tukey's Honestly Significant Differences (HSD): This method is used in ANOVA (Analysis of Variance) to determine which group means are significantly different from each other. While Tukey's HSD addresses multiple comparisons, it is specific to ANOVA and not a correction method for inflated alpha values. Thus, B is not the correct answer.
C. Post Hoc Testing: This term refers to conducting additional tests after an initial analysis to explore specific differences between groups. While it is related to addressing multiple comparisons, it is not a conservative correction method for inflated alpha values. Hence, C is not the correct answer.
D. Bonferroni Correction: This is a conservative method for addressing the issue of inflated alpha values in multiple comparisons. It adjusts the significance level to maintain an overall desired level of type I error rate. It accounts for the increased chance of obtaining false positives by dividing the desired alpha level by the number of tests conducted. Therefore, D is the correct answer.
In summary, when facing the scenario of inflated alpha values due to multiple comparisons, the conservative correction method to use is the Bonferroni correction (Option D).