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<p>Using minimal replications in the design of experiments for biological research can be advantageous, especially when resources are limited or when ethical considerations limit the number of experimental units (e.g., animals or plants). In biological research, there are often ethical constraints on the use of animals or plants. Minimizing the number of replications can help reduce the total number of subjects or specimens required for the study. To deal such situations, this study introduces two novel nested block design series with minimal replications, that is, each with treatments or varieties replicated no more than seven times. Nested block designs are also used in experimental settings where two factors cause heterogeneity and one of them is nested within the other. A Statistical Analysis System (SAS) program has also been written to facilitate the easy computation of variances and canonical efficiency factors for the proposed designs.</p>

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Minimally Replicated Nested Block Designs for Biological Experiments

  • 期刊论文

  • 发表日期：

    2026年3月30日

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  • Vinayaka,
  • B. N. Mandal,
  • Rajender Parsad,
  • P. Murali

摘要

Using minimal replications in the design of experiments for biological research can be advantageous, especially when resources are limited or when ethical considerations limit the number of experimental units (e.g., animals or plants). In biological research, there are often ethical constraints on the use of animals or plants. Minimizing the number of replications can help reduce the total number of subjects or specimens required for the study. To deal such situations, this study introduces two novel nested block design series with minimal replications, that is, each with treatments or varieties replicated no more than seven times. Nested block designs are also used in experimental settings where two factors cause heterogeneity and one of them is nested within the other. A Statistical Analysis System (SAS) program has also been written to facilitate the easy computation of variances and canonical efficiency factors for the proposed designs.