Unexpected failures of recommended tests in basic statistical analyses of ecological data

Kikvidze, Zaal და Moya-Laraño, Jordi (2008) Unexpected failures of recommended tests in basic statistical analyses of ecological data. Web Ecology, 8. С. 67-73. ISSN 1399-1183

მოცემული მასალის ბოლო ვერსია.

Kikvidze & Moya-Larano 2008 Web_Ecol.8.67-73.pdf

Download (286kB) | გადახედვა


Ecologists, when analyzing the output of simple experiments, often have to compare statistical samples that simultaneously are of uneven size, unequal variance and distribute non-normally. Although there are special tests designed to address each of these unsuitable characteristics, it is unclear how their combination affects the tests. Here we compare the performance of recommended tests using generated data sets that simulate statistical samples typical in ecological research. We measured rates of type I and II errors, and found that common parametric tests such as ANOVA are quite robust to non-normality, uneven sample size, unequal variance, and their effect combined. ANOVA and randomization tests produced very similar results. At the same time, the t-test for unequal variance unexpectedly lost power with samples of uneven size. Also, non-parametric tests were strongly affected by unequal variance in large samples, yet non-parametric tests could complement parametric tests when testing samples of uneven size. Thus, we demonstrate that the robustness of each kind of test strongly depends on the combination of parameters (distribution, sample size, equality of variances). We conclude that manuals should be revised to offer more elaborate instructions for applying specific statistical tests.

ობიექტის ტიპი: სტატია
თემატიკა: Q Science > Ecology
ქვეგანყოფილება: Institutes > 4D Research Institute
განმათავსებელი მომხმარებელი: Prof. Zaal Kikvidze
განთავსების თარიღი: 16 აპრილი 2015 06:20
ბოლო ცვლილება: 16 აპრილი 2015 06:20
URI: http://eprints.iliauni.edu.ge/id/eprint/2048

ამ მასალაზე ხელმისაწვდომი ვერსია

Actions (login required)

ობიექტის ნახვა ობიექტის ნახვა