Answers are grounded in this paper and cite their sources.
Statistical modeling study demonstrates power requirements and dose spacing to distinguish binary response curves, highlighting the need for large sample sizes.
The logistic and integrated normal binary response curves are known to agree closely except in the tails. For experiments based on three dose levels the power of a signifacance test is found for the null hypothesis that the response curve is ligistic against the alternative that it is normal, and vice versa. From this an appropriate spacing of dose levels for discrimination is found. Approximately 1000 observations are necessary for even modest sensitivity.
No takes yet. Share an insight, caveat, or question.
Chambers et al. (1967) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: