Assessing the validity of a statistical distribution: some illustrative examples from dermatological research.
BACKGROUND
Assuming a statistical distribution is one of the key points before conducting a statistical analysis. Goodness-of-fit tests are used to assess the validity of an assumed statistical distribution. In dermatological research, the goodness-of-fit tests used are less powerful.


OBJECTIVE
We recommend the use of some specific goodness-of-fit tests for various distributions. A graphical technique called quantile-quantile plotting is introduced as an additional tool to assess the validity of an assumed distribution. We show why one should be careful in selecting a goodness-of-fit method by giving some relevant examples.


METHODS
Goodness-of-fit tests for testing normal and non-normal distributions are introduced. Quantile-quantile plots were constructed, and we conducted a simulation study for testing normality.


RESULTS
We found that the Shapiro-Wilk statistic is the most powerful test overall to test for normal distribution. Quantile-quantile plotting is a very effective graphical technique to identify a distribution for a dataset.


CONCLUSIONS
The use of the Shapiro-Wilk test and quantile-quantile plotting is recommended for testing normality.
Sürücü
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Department of Statistics, Middle East Technical University, Ankara, Turkey. sbaris@metu.edu.tr
Koç
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D000293:Adolescent; D000328:Adult; D003880:Dermatology / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D012106:Research / Q000706:statistics & numerical data*; D016008:Statistical Distributions; D054928:Validation Studies as Topic