100 ms response time bins reduced the largest 500 ms capped mean stop time ranges in 223 of 226 finite independent AOMIC PIOP2 race models with exact go and summary probabilities

We tested how removal of response times changes information about stop time. We used all 226 task designs in OpenNeuro ds002790 version 2.0.0. Each model has a known finite go law and an independent nonnegative stop law. The target is the mean stop time capped at 500 ms. Exact response probabilities are treated as known. We proved sharp finite programs for each recorded summary. The median largest possible target range was 23.87 ms with outcomes at each delay. It was 5.00 ms with 100 ms response time bins at each delay. The range decreased in 223 of 226 designs. The median paired percentage decrease was 77.36 percent. Full response times gave a median largest range of 4.00 ms. The additional checks use the first 90 designs in source order. Source hash checks and numerical certificate checks are preserved. The first 90 primary designs were repeated from fresh source files. These are model information limits. They do not estimate human stop times or finite-sample precision.

stop-signal task · response inhibition · partial identification · sharp bounds · response time bins · race model · finite distributions · cognitive neuroscience