Multiple comparisons occur when we test multiple hypotheses, whether in a series of multi-group pairwise comparisons or a series of hypothesis tests. While there is a rich and vibrant discussion as to when and where it is most appropriate to address multiple comparisons and preserving our type I error rate, we focus on introducing the general concept and some potential post-hoc solutions (more of which will be covered in our ANOVA-related lecture).
The false discovery rate is another approach to control for multiple comparisons and is introduced in greater detail with examples by "hand" and in R.
A video for the Biostatistical Methods I (BIOS 6611) course in the Department of Biostatistics and Informatics at the University of Colorado-Anschutz Medical Campus taught by Dr. Alex Kaizer. Slides and additional material available at [ Ссылка ].
Table of Contents:
00:00 - Intro Song
00:18 - Welcome
00:37 - Multiple Comparisons
04:33 - Some Post-Hoc Comparison Methods
05:54 - False Discovery Rate
07:32 - FDR Algorithm
08:33 - FDR Example
11:41 - Multiple Corrections in R and SAS
12:41 - The FDR Example in R
