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  "Title": "Augmented Pooled Randomized Complete Block Design Analysis",
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  "Description": "Augmented randomized complete block designs (augmented\nRCBDs) are useful for researchers to evaluate large numbers of\nunreplicated test entries with limited replicated checks. This\nR and 'Shiny'-based statistical package provides methods for\nthe analysis of augmented randomized complete block designs\n(augmented RCBDs) across multiple environments. The package\nperforms environment-wise augmented RCBD analysis and pooled\nanalysis across environments, including analysis of variance\n(ANOVA), testing for homogeneity of error variances across\nenvironments, adjusted treatment means, treatment\nsum-of-squares partitioning, standard error of the mean (SEM),\ncritical difference (CD), and treatment ranking. For pooled\nanalysis, environment-specific error variances are assessed for\nhomogeneity and used for appropriate transformation where\nrequired, followed by a general linear model incorporating\nenvironment, block nested within environment, treatment, and\nenvironment x treatment interaction. This 'Shiny' interface\nprovides a user-friendly platform that enables researchers and\nplant breeders to perform these analyses without requiring\nextensive programming knowledge. For method details see,\nFederer, W. T. (1961) <doi:10.2307/2527837>. It consists of the\nfunction augmentedPooledRCBD() which launches the application\ninterface.",
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