Type II error
Failing to reject the null hypothesis when it should be rejected, a false negative
Type II errors are most prevalent when it comes to smaller sample sizes. Small samples sizes often do not all of for enough statistical power to detect significant effects. When non-significant findings are found, it is often wise to run a post hoc power analysis on the yielded values to see what statistical power was achieved. More cases or observations of the outcome may need to be collected for a statistically or clinically meaningful effect can be detected.
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