The researchers studied ways to improve the detection of effects in statistical tests when many tests are conducted. They compared different methods of controlling errors, like the false discovery rate, to traditional methods. They found that the false discovery rate methods had better power to detect real effects, even when set at the standard significance level. They recommend using these methods when dealing with a large number of tests.