Statistical Designs in R

1- Complete Randomized Design (CRD)

1.1 Analysis of Variance 

aku<-lm(POD~treatment, data=data_shahzad_4)

1.2 Multiple comparisons Test

aov.out<- aov(POD~treatment, data=data_shahzad_4)
LSD.test(aov.out,"treatment", console = TRUE)

2.Randomized Complete Block Design

2.1 Analysis of Variance

wina<- lm (POD~treatment+replication, data=data_shahzad_4)
anova(wina)

2.2 Multiple Comparison Test

LSD.test(winams,"treatment", console = TRUE)

3. RCBD Factorial Design 

3.1 Analysis of Variance

wina<- lm (POD~treatment+replication+variety+treatment:variety, data=data_shahzad_4)
anova(wina)

3.2 Multiple comparison test

LSD.test(data_shahzad_4$POD,
         data_shahzad_4$treatment:data_shahzad_4$variety, 
         54.2, 78, console = TRUE)

4. Liner mixed model

4.1 Analysis of Variance

data_shahzad_4$plot <- factor(c(1:48,1:48))
POD.rlme <- lme(POD ~ Year*treatment*variety + replication, 
                random = ~1|plot/Year/replication,
                data=data_shahzad_4)
anova(POD.rlme)

4.2 multiple comparisons Test

POD.rlsm <- lsmeans(POD.rlme, ~Year*treatment*variety, adjust="tukey")
POD.rcld <- cld(POD.rlsm, alpha=0.05, Letters=letters, adjust="tukey")
POD.rt <- POD.rcld[,c(1:4,9)]
POD.rt

5 RCBD Split Plot Design

kebe<-with(data_irfan,sp.plot(replication,Treatment,varities,plant_height))

anova(kebe<)

gla<-kebe$gl.a
glb<-kebe$gl.b
Ea<-kebe$gl.a
Eb<-kebe$gl.b

5.2 Multiple Comparison Test

5.2.1 Main effect of Treatment

ms<-with(data_irfan,LSD.test(plant_height,Treatment,gla,Ea, console = TRUE))

5.2.2 Main effect of a variety

ms<-with(data_irfan,LSD.test(plant_height,varities,glb,Eb, console = TRUE))

5.2.3 Interaction of Treatment and variety

ms<-with(data_irfan,LSD.test(plant_height,Treatment:varities,glb,Eb, console = TRUE))