# Analysis of Variance and Other Important Complementary Analyzes Perform analysis of variance and other important complementary analyzes. The functions are easy to use. Performs analysis in various designs, with balanced and unbalanced data. package ## Details ||| |:--|:--| |Package:|easyanova| |Type:|Package| |Version:|11.0| |Date:|2024-09-14| |License:|GPL-2| ## Author(s) Emmanuel Arnhold ## References CRUZ, C.D. and CARNEIRO, P.C.S. Modelos biometricos aplicados ao melhoramento genetico. 2nd Edition. Vicosa, UFV, v.2, 2006. 585p. KAPS, M. and LAMBERSON, W. R. Biostatistics for Animal Science: an introductory text. 2nd Edition. CABI Publishing, Wallingford, Oxfordshire, UK, 2009. 504p. SAMPAIO, I. B. M. Estatistica aplicada a experimentacao animal. 3nd Edition. Belo Horizonte: Editora FEPMVZ, Fundacao de Ensino e Pesquisa em Medicina Veterinaria e Zootecnia, 2010. 264p. SANDERS W.L. and GAYNOR, P.J. Analysis of switchback data using Statistical Analysis System, Inc. Software. Journal of Dairy Science, 70.2186-2191. 1987. PIMENTEL-GOMES, F. and GARCIA C.H. Estatistica aplicada a experimentos agronomicos e florestais: exposicao com exemplos e orientacoes para uso de aplicativos. Editora Fealq, v.11, 2002. 309p. RAMALHO, M. A. P.; FERREIRA, D. F. and OLIVEIRA, A. C. Experimentacao em Genetica e Melhoramento de Plantas. Editora UFLA, 2005, 322p. ## See Also ea1, ea2, ec ## Examples ```r # Kaps and Lamberson(2009) data(data1) data(data2) data(data3) data(data4) # analysis in completely randomized design r1<-ea1(data1, design=1) names(r1) r1 # analysis in randomized block design r2<-ea1(data2, design=2) # analysis in latin square design r3<-ea1(data3, design=3) # analysis in several latin squares design r4<-ea1(data4, design=4) r1[1] r2[1] r3[1] r4[1] # analysis in unbalanced randomized block design response<-ifelse(data2$Gain>850, NA, data2$Gain) ndata<-data.frame(data2[-3],response) ndata r5<-ea1(ndata, design=2 ) r5 # multivariable response (list argument = TRUE) t<-c('a','a','a','b','b','b','c','c','c') r1<-c(10,12,12.8,4,6,8,14,15,16) r2<-c(102,105,106,125,123,124,99,95,96) r3<-c(560,589,590,658,678,629,369,389,378) d<-data.frame(t,r1,r2,r3) results=ea1(d, design=1, list=TRUE) names(results) results results[1][[1]] names(results[1][[1]]) ```

easyanova-package