Psicothema· 2017Q1
Non-normal data: Is ANOVA still a valid option?
- 1,534citations
- Q1SCImago
- 2017year
Short summary
The F-test in ANOVA remains robust to Type I error even with non-normal data across various health and social science distributions, according to a large-scale Monte Carlo simulation.
AI-generated from the title and abstract; the full text is not read.
Key points
- ANOVA's F-test shows 100% robustness to Type I error across all tested conditions.
- Robustness was evaluated using a Monte Carlo simulation with three groups and various common health/social science distributions.
- Tested conditions included equal/unequal sample sizes, distribution shapes, and contamination levels.
- Results indicate the F-test is reliable regardless of normality violations in the data.
AI-generated from the title and abstract; the full text is not read.
Abstract
BACKGROUND: The robustness of F-test to non-normality has been studied from the 1930s through to the present day. However, this extensive body of research has yielded contradictory results, there being evidence both for and against its robustness. This study provides a systematic examination of F-test robustness to violations of normality in terms of Type I error, considering a wide variety of distributions commonly found in the health and social sciences. METHOD: We conducted a Monte Carlo simulation study involving a design with three groups and several known and unknown distributions. The manipulated variables were: Equal and unequal group sample sizes; group sample size and total sample size; coefficient of sample size variation; shape of the distribution and equal or unequal shapes of the group distributions; and pairing of group size with the degree of contamination in the distribution. RESULTS: The results showed that in terms of Type I error the F-test was robust in 100% of the cases studied, independently of the manipulated conditions.
The authors' abstract, as published at the source. Psicothema, 2017 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Field: Statistics and Probability
Statistics and ProbabilityMathematics