Package: AugmentedPooledRCBD 0.1.0

AugmentedPooledRCBD: Augmented Pooled Randomized Complete Block Design Analysis

Augmented randomized complete block designs (augmented RCBDs) are useful for researchers to evaluate large numbers of unreplicated test entries with limited replicated checks. This R and 'Shiny'-based statistical package provides methods for the analysis of augmented randomized complete block designs (augmented RCBDs) across multiple environments. The package performs environment-wise augmented RCBD analysis and pooled analysis across environments, including analysis of variance (ANOVA), testing for homogeneity of error variances across environments, adjusted treatment means, treatment sum-of-squares partitioning, standard error of the mean (SEM), critical difference (CD), and treatment ranking. For pooled analysis, environment-specific error variances are assessed for homogeneity and used for appropriate transformation where required, followed by a general linear model incorporating environment, block nested within environment, treatment, and environment x treatment interaction. This 'Shiny' interface provides a user-friendly platform that enables researchers and plant breeders to perform these analyses without requiring extensive programming knowledge. For method details see, Federer, W. T. (1961) <doi:10.2307/2527837>. It consists of the function augmentedPooledRCBD() which launches the application interface.

Authors:Santosha Rathod [aut, cre, ctb], Susheel Kumar Sarkar [aut, ctb], Bijoy Chanda [aut, ctb], Bellamkonda Jyostna [aut], Sayantani Karmakar [aut], Vishnu Shankar [aut], Santosh Ganapati Patil [aut], Prabhat Kumar [aut], Prashant Vikram [aut], Mrinmoy Ray [aut], Nobin Chandra Paul [aut], Anil Kumar [aut]