{Reference Type}: Journal Article
{Title}: Why is a small sample size not enough?
{Author}: Cao Y;Chen RC;Katz AJ;
{Journal}: Oncologist
{Volume}: 0
{Issue}: 0
{Year}: 2024 Jun 27
{Factor}: 5.837
{DOI}: 10.1093/oncolo/oyae162
{Abstract}: <B>BACKGROUND: </B>Clinical studies are often limited by resources available, which results in constraints on sample size. We use simulated data to illustrate study implications when the sample size is too small.<BR><B>RESULTS: </B>Using 2 theoretical populations each with N = 1000, we randomly sample 10 from each population and conduct a statistical comparison, to help make a conclusion about whether the 2 populations are different. This exercise is repeated for a total of 4 studies: 2 concluded that the 2 populations are statistically significantly different, while 2 showed no statistically significant difference.<BR><B>CONCLUSIONS: </B>Our simulated examples demonstrate that sample sizes play important roles in clinical research. The results and conclusions, in terms of estimates of means, medians, Pearson correlations, chi-square test, and P values, are unreliable with small samples.