A warning about statistical significance tests performed on large samples of nonindependent observations.
When sample observations are not independent, the variance estimate in the denominator of the Student t statistic is altered, inflating the value of the test statistic and resulting in far too many Type I errors. Furthermore, how much the Type I error probability exceeds the nominal significance level is an increasing function of sample size. If N is quite large, in the range of 100 to 200 or larger, small apparently inconsequential correlations that are unknown to a researcher, such as .01 or .02, can have substantial effects and lead to false reports of statistical significance when effect size is zero.
Zimmerman
Donald W
DW
Carleton University, USA. donzimmer@midmaine.com
D006801:Humans; D008962:Models, Theoretical; D019370:Observation