Non-normal Distributions Commonly Used in Health, Education, and Social Sciences: A Systematic Review

• Main Authors: Roser Bono, María J. Blanca, Jaume Arnau, Juana Gómez-Benito
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2017-09-01
• Series: Frontiers in Psychology
• Subjects: non-normal distributions; gamma distribution; negative binomial distribution; multinomial distribution; binomial distribution; lognormal distribution
• Online Access: http://journal.frontiersin.org/article/10.3389/fpsyg.2017.01602/full

Statistical analysis is crucial for research and the choice of analytical technique should take into account the specific distribution of data. Although the data obtained from health, educational, and social sciences research are often not normally distributed, there are very few studies detailing which distributions are most likely to represent data in these disciplines. The aim of this systematic review was to determine the frequency of appearance of the most common non-normal distributions in the health, educational, and social sciences. The search was carried out in the Web of Science database, from which we retrieved the abstracts of papers published between 2010 and 2015. The selection was made on the basis of the title and the abstract, and was performed independently by two reviewers. The inter-rater reliability for article selection was high (Cohen’s kappa = 0.84), and agreement regarding the type of distribution reached 96.5%. A total of 262 abstracts were included in the final review. The distribution of the response variable was reported in 231 of these abstracts, while in the remaining 31 it was merely stated that the distribution was non-normal. In terms of their frequency of appearance, the most-common non-normal distributions can be ranked in descending order as follows: gamma, negative binomial, multinomial, binomial, lognormal, and exponential. In addition to identifying the distributions most commonly used in empirical studies these results will help researchers to decide which distributions should be included in simulation studies examining statistical procedures.