PMID- 33335808
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20201219
IS  - 2167-8359 (Print)
IS  - 2167-8359 (Electronic)
IS  - 2167-8359 (Linking)
VI  - 8
DP  - 2020
TI  - Comparing multiple comparisons: practical guidance for choosing the best multiple 
      comparisons test.
PG  - e10387
LID - 10.7717/peerj.10387 [doi]
LID - e10387
AB  - Multiple comparisons tests (MCTs) include the statistical tests used to compare 
      groups (treatments) often following a significant effect reported in one of many 
      types of linear models. Due to a variety of data and statistical considerations, 
      several dozen MCTs have been developed over the decades, with tests ranging from 
      very similar to each other to very different from each other. Many scientific 
      disciplines use MCTs, including >40,000 reports of their use in ecological 
      journals in the last 60 years. Despite the ubiquity and utility of MCTs, several 
      issues remain in terms of their correct use and reporting. In this study, we 
      evaluated 17 different MCTs. We first reviewed the published literature for 
      recommendations on their correct use. Second, we created a simulation that 
      evaluated the performance of nine common MCTs. The tests examined in the 
      simulation were those that often overlapped in usage, meaning the selection of 
      the test based on fit to the data is not unique and that the simulations could 
      inform the selection of one or more tests when a researcher has choices. Based on 
      the literature review and recommendations: planned comparisons are overwhelmingly 
      recommended over unplanned comparisons, for planned non-parametric comparisons 
      the Mann-Whitney-Wilcoxon U test is recommended, Scheffe's S test is recommended 
      for any linear combination of (unplanned) means, Tukey's HSD and the Bonferroni 
      or the Dunn-Sidak tests are recommended for pairwise comparisons of groups, and 
      that many other tests exist for particular types of data. All code and data used 
      to generate this paper are available at: 
      https://github.com/stevemidway/MultipleComparisons.
CI  - (c)2020 Midway et al.
FAU - Midway, Stephen
AU  - Midway S
AD  - Department of Oceanography and Coastal Sciences, Louisiana State University, 
      Baton Rouge, LA, United States of America.
FAU - Robertson, Matthew
AU  - Robertson M
AD  - Centre for Fisheries Ecosystems Research, Fisheries and Marine Institute of 
      Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, 
      Canada.
FAU - Flinn, Shane
AU  - Flinn S
AD  - Quantitative Fisheries Center, Department of Fisheries and Wildlife, Michigan 
      State University, East Lansing, MI, United States of America.
FAU - Kaller, Michael
AU  - Kaller M
AD  - School of Renewable Natural Resources and Department of Experimental Statistics, 
      Louisiana State University Agricultural Center, Baton Rouge, LA, United States of 
      America.
LA  - eng
PT  - Journal Article
DEP - 20201204
PL  - United States
TA  - PeerJ
JT  - PeerJ
JID - 101603425
PMC - PMC7720730
OTO - NOTNLM
OT  - ANOVA
OT  - Bonferroni
OT  - Contrasts
OT  - Multiple comparisons
OT  - Scheffe
OT  - Tukey HSD
COIS- The authors declare there are no competing interests.
EDAT- 2020/12/19 06:00
MHDA- 2020/12/19 06:01
PMCR- 2020/12/04
CRDT- 2020/12/18 05:51
PHST- 2020/07/20 00:00 [received]
PHST- 2020/10/27 00:00 [accepted]
PHST- 2020/12/18 05:51 [entrez]
PHST- 2020/12/19 06:00 [pubmed]
PHST- 2020/12/19 06:01 [medline]
PHST- 2020/12/04 00:00 [pmc-release]
AID - 10387 [pii]
AID - 10.7717/peerj.10387 [doi]
PST - epublish
SO  - PeerJ. 2020 Dec 4;8:e10387. doi: 10.7717/peerj.10387. eCollection 2020.