Statistical Models in R (ANOVA & Multiple Comparison Tests)

 

Statistical Model in R
	Linear Mixed Model
ANOVA	POD<- lme(POD ~ Year*treatment*variety + replication, random = ~1|plot/Year/replication, data=dataset) anova(POD)
Multiple Comparison	POD.rlsm <- lsmeans(POD, ~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
Complete Randomized Design (CRD)
ANOVA	aku<-lm(POD~treatment, data=dataset) anova(aku)
Multiple Comparison test	aov.out<- aov(POD~treatment, data=dataset) LSD.test(aov.out,"treatment", console = TRUE)
Randomized Complete Block Design (RCBD)
ANOVA	wina<- lm (POD~treatment+replication, data=dataset) anova(wina)
Multiple Comparison test	LSD.test(winams,"treatment", console = TRUE)
RCBD Split-Plot Design
ANOVA	kebe<-with(dataset,sp.plot(replication,treatment,variety,POD))
Initial working	gla<-kebe$gl.a glb<-kebe$gl.b Ea<-kebe$gl.a Eb<-kebe$gl.b
First factor	ms<-with(data_shahzad_4,LSD.test(POD,treatment,gla,Ea, console = TRUE))
Second factor	ms<-with(data_shahzad_4,LSD.test(POD,variety,glb,Eb, console = TRUE))
Interaction	ms<-with(data_shahzad_4,LSD.test(POD,treatment:variety,glb,Eb, console = TRUE))
RCBD Factorial Design
ANOVA	wina<- lm (POD~treatment+replication+variety+treatment:variety, data=dataset)
Multiple Comparison test	LSD.test(dataset$POD,dataset$treatment:dataset$variety, 54.2, 78, console = TRUE) 54.2= Mean square error 78= Degree of freedom