Multiplicity problems emerge from investigators looking at many additional endpoints and treatment group comparisons. Thousands of potential comparisons can emanate from one trial. Investigators might only report the significant comparisons, an unscientific practice if unwitting, and fraudulent if intentional. Researchers must report all the endpoints analysed and treatments compared. Some statisticians propose statistical adjustments to account for multiplicity. Simply defined, they test for no effects in all the primary endpoints undertaken versus an effect in one or more of those endpoints. In general, statistical adjustments for multiplicity provide crude answers to an irrelevant question. However, investigators should use adjustments when the clinical decision-making argument rests solely on one or more of the primary endpoints being significant. In these cases, adjustments somewhat rescue scattershot analyses. Readers need to be aware of the potential for under-reporting of analyses.