In this article, the authors compare the assay performance measures, signalwindow, Z' factor, and assay variability ratio. They examine their mathematical formulae for similarities and differences, describe their statistical sampling properties using the results of a computer simulation, and illustrate their usewith example data. Based on these results, the authors recommend the Z' factor as a preferredmeasure of assay performance for screening assays and point out that none of thesemeasures are adequate for characterizing concentration-response assays.
Sittampalam SG, Iversen PW, Boadt JA, Kahl SD, Bright A, Zock JM, et al: Design of signal windows in high throughput screening assays for drug discovery. J Biomol Screen1997;2:159-169.
2.
Zhang JH, Chung TDY, Oldenburg KR: Asimple statistical parameter for use in evaluation and validation of high throughput screening assays. J Bimol Screen1999;4:67-73.
3.
Taylor PB, Stewart FP, Dunnington DJ, Quinn ST, Shultz CK, Vaidya KS, et al: Automated assay optimization with integrated statistics and smart robotics. J Biomol Screen2000;5:213-225.
4.
Zhang JH, Chung TDY, Oldenburg KR: Confirmation of primary active substances from high throughput screening of chemical and biological populations: a statistical approach and practical considerations. J Comb Chem2000;2:258-265.
5.
Eastwood BJ, Farmen MW, Iversen PW, Craft TJ, Smallwood JK, Garbison KE, et al: Theminimum significant ratio: a statistical parameter to characterize the reproducibility of potency estimates from concentration-response assays and estimation by replicate-experiment studies. J Biomol Screen2006;11:253-261.
6.
Bland JM, Altman DG: Statistical methods for assessing agreement between two methods of clinical measurement. Lancet1986;1:307-310.
