Recognition heuristics
How accurate is the recognition heuristic? Figure 2a shows the relationship between recognition validity (i.e., PPV) and discriminability (i.e., d’ ). As expected, the greater d’ , the greater the separation between signal and noise. However, the degree of separation is relatively modest, with maximumd’ ~1.0. Fig 2b displays the relationship betweend’ and TE value. The optimal cut-off is approximatelylog(OR) of 1, which is equivalent to jnd as per the Weber-Fechner law. Similarly, the largest evidentiary support is found for TE of about 1( =1.17) at moderate p=0.033. P-values for larger TE, which theoretically should have higher recognition validity, has not reached traditional statistical evidence at p<0.05 (Fig 2c), which probably explains why larger treatment effects are not invariably associated with drug approval without testing in RCTs. In fact, only 11 observations were associated with effect size exceeding\(\operatorname{}\text{OR}>2\).