positive or negative controls can adversely affect the Z-factor, potentially leading to an apparently unfavorable Z-factor even when the assay would perform well in actual screening . In addition, the application of the single Z-factor-based criterion to two or more positive controls with different strengths in the same assay will lead to misleading results . The absolute sign in the Z-factor makes it inconvenient to derive the statistical inference of Z-factor mathematically . A recently proposed statistical parameter, strictly standardized mean difference (SSMD), can address these issues . One estimate of SSMD is robust to outliers. See also high-throughput screening SSMD Z-score or Standard score References Further reading Kraybill, B. (2005) "Quantitative Assay Evaluation and Optimization" (unpublished note) Zhang XHD (2011) "Optimal High-Throughput Screening: Practical Experimental Design and Data Analysis for Genome-scale RNAi Research, Cambridge University Press" Change detection Effect size Biological techniques and tools Statistical analysis Pharmaceutical industry Sample statistics