I will introduce how to perform a Two-Way ANOVA analysis using SAS Studio. Here is the data that you have available:
Cultivar Nitrogen Block Yield 1 CV1 N0 I 99 2 CV1 N0 II 109 3 CV1 N0 III 89 4 CV1 N1 I 115 5 CV1 N1 II 142 6 CV1 N1 III 133 7 CV1 N2 I 121 8 CV1 N2 II 157 9 CV1 N2 III 142 10 CV1 N3 I 125 11 CV1 N3 II 150 12 CV1 N3 III 139 13 CV2 N0 I 82 14 CV2 N0 II 104 15 CV2 N0 III 99 16 CV2 N1 I 117 17 CV2 N1 II 125 18 CV2 N1 III 127 19 CV2 N2 I 145 20 CV2 N2 II 154 21 CV2 N2 III 154 22 CV2 N3 I 151 23 CV2 N3 II 166 24 CV2 N3 III 175
<strong># </strong>Download the above data to Excel using R
Cultivar= rep(c("CV1","CV2"),each=12)
Nitrogen= rep(rep(c("N0","N1","N2","N3"), each=3),2)
Block= rep(c("I","II","III"),8)
Yield= c (99, 109, 89, 115, 142, 133, 121, 157, 142, 125, 150, 139, 82, 104, 99, 117, 125, 127, 145, 154, 154, 151, 166, 175)
dataA= data.frame(Cultivar,Nitrogen,Block,Yield)
install.package("writexl")
library(writexl)
write_xlsx (DataA,"<span style="background-color:rgba(0, 0, 0, 0)" class="has-inline-color has-vivid-red-color">C:/Users/LG/Desktop</span>/dataA.xlsx")
<span style="background-color:rgba(0, 0, 0, 0)" class="has-inline-color has-vivid-red-color"># Please confirm the directory path on your computer</span>
Upload this Excel file to SAS Studio. After uploading the Excel file to SAS Studio, create a data table named “EXP1” in My Libraries. Then, click on the EXP1 data table. Then, select the icon for generating code located at the top.
By doing so, a new tab named “Program 1” will be created, allowing you to generate the code.
Indeed, R Studio provides essential statistical modeling tools that enable you to select variables based on the model and examine statistical outcomes without the need to write code. However, in this case, I will demonstrate the process of performing ANOVA using SAS code. Let’s input the following code into the code editor and execute it.
<strong>proc glm </strong><span class="has-inline-color has-vivid-cyan-blue-color">data</span>= DATABASE.EXP1; <span class="has-inline-color has-vivid-cyan-blue-color">class</span> Block Cultivar Nitrogen; <span class="has-inline-color has-vivid-cyan-blue-color">model</span> Yield= Cultivar Nitrogen Cultivar*Nitrogen / <span class="has-inline-color has-vivid-cyan-blue-color">ss1 ss3</span>; <span class="has-inline-color has-vivid-cyan-blue-color">lsmeans</span> Cultivar Nitrogen / <span class="has-inline-color has-vivid-cyan-blue-color">adjust</span>=tukey <span class="has-inline-color has-vivid-cyan-blue-color">pdiff</span>=all <span class="has-inline-color has-vivid-cyan-blue-color">alpha</span>=0.05 <span class="has-inline-color has-vivid-cyan-blue-color">cl</span>; <strong>quit;</strong>
I will verify the accuracy of the above results using R.
ANOVA= aov(Yield ~ Cultivar + Nitrogen + Cultivar:Nitrogen + factor(Block), data=dataA) summary(ANOVA)
