Meta-Research: Why we need to report more than 'Data were Analyzed by t-tests or ANOVA'
- Mayo Clinic, United States
- Charité - Universitätsmedizin Berlin, Berlin Institutes of Health, Germany
- Medical Faculty, University of Belgrade, Serbia
-
Download
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Meta-Research: Why we need to report more than 'Data were Analyzed by t-tests or ANOVA'eLife 7:e36163.https://doi.org/10.7554/eLife.36163 - Cite
- CommentOpen annotations (there are currently 0 annotations on this page).
Figures
Figure 1
Systematic review flow chart.
The flow chart illustrates the selection of articles for inclusion in this analysis at each stage of the screening process.
-
Figure 1—source data 1
Data from systematic review.
- https://doi.org/10.7554/eLife.36163.003
Figure 2
Many papers lack the information needed to determine what type of ANOVA was performed.
The figure illustrates the proportion of papers in our sample that reported information needed to determine what type of ANOVA was performed, including the number of factors, the names of factors, …
Figure 3
Why it matters whether investigators use a one-way vs two-way ANOVA for a study design with two factors.
The two-way ANOVA allows investigators to determine how much of the variability explained by the model is attributed to the first factor, the second factor, and the interaction between the two …
Figure 4
Additional implications of using a one-way vs two-way ANOVA.
This figure compares key features of one- and two-way ANOVAs to illustrate potential problems with using a one-way ANOVA for a design with two or more factors. When used for a study with two …
Figure 5
Why it matters whether investigators used an ANOVA with vs. without repeated measures.
This figure highlights the differences between ANOVA with vs. without repeated measures and illustrates the problems with using an ANOVA without repeated measures when the study design includes …
Figure 6
Why papers need to contain sufficient detail to confirm that the appropriate t-test was used.
This figure highlights the differences between unpaired and paired t-tests by illustrating how these tests interpret the data differently, test different hypotheses, use information differently when …
Figure 7
Differences between the results of statistical tests depend on the data.
The three datasets use different pairings of the values shown in the dot plot on the left. The comments on the right side of the figure illustrate what happens when an unpaired t-test is …
Figure 8
Few papers report the details needed to confirm that the result of the ANOVA was correct.
This figure reports the proportion of papers with ANOVAs (n = 225) that reported the F-statistic, degrees of freedom and exact p-values. Sometimes indicates that the information was reported for …
Tables
Table 1
Reporting of details needed to verify the results of a t-test.
https://doi.org/10.7554/eLife.36163.013| Reported t-statistic | Reported exact sample size or degrees of freedom | Reported exact p-values | |
|---|---|---|---|
| No | 156 (95.7%) | 11 (6.7%) | 113 (69.3%) |
| Sometimes | 0 | 27 (16.6%) | 17 (10.4%) |
| Yes | 7 (4.3%) | 125 (76.7%) | 33 (20.2%) |
-
We analyzed the 179 papers in our sample that included t-tests to check if they reported the details that are needed to verify the results of these tests: we had to exclude 16 papers from this analysis because we were unable to determine what data were analyzed by t-tests or to identify a two-group comparison. Most of the papers (95.7%; 156/163) did not report the t-statistic (column 2) and over two-thirds (69.3%; 113/163) did not report exact p-values (column 4), but over three-quarters (76.7%; 125/163) reported the exact sample size or degree of freedom for all of the t-tests in the paper (column 3).
Additional files
-
Supplementary file 1
Number of articles examined by journal.
- https://doi.org/10.7554/eLife.36163.014
-
Supplementary file 2
Abstraction protocol for systematic review.
- https://doi.org/10.7554/eLife.36163.015
-
Transparent reporting form
- https://doi.org/10.7554/eLife.36163.016
-
Reporting standard 1
PRISMA 2009 checklist.
- https://doi.org/10.7554/eLife.36163.017
