data=read.csv(“D:/RESEARCH-2/STATISTIC/Analyse/BH/NORT/1fKO1.csv”) attach(data) head(data) names(data) summary(data) data\(Group=as.factor(data\)Group) data\(Genotype=as.factor(data\)Genotype) data\(time=as.factor(data\)time) data\(TimexGenotype=as.factor(data\)TimexGenotype) data\(Group2=as.factor(data\)Group2) library(FSA) Sum = Summarize(RI1H ~ Group + TimexGenotype , data=data, digits=3) Sum\(se = Sum\)sd / sqrt(Sum\(n) Sum\)se = signif(Sum$se, digits=3) Sum
library(DescTools) fm1 <- aov(RI1H ~ Group,data=data) summary(fm1) library(DescTools) fm1 <- aov(RI24H ~ Group,data=data) summary(fm1) PostHocTest(fm1, method = “bonferroni”) PostHocTest(fm1, method = “hsd”) PostHocTest(fm1, method = “scheffe”) DunnettTest(DT ~ Group1,data=data) PostHocTest(fm1, method = “duncan”) PostHocTest(fm1, method = “lsd”) PostHocTest(fm1, method = “newmankeuls”) #two way anova:
model =lm(RI1H ~ Group + Genotype, data=data) anova(model)
model = lm(RI1H ~ GroupGenotype, data=data) m=anova(model) model = lm(RI1H ~ Grouptime, data=data) m=anova(model) m
model = lm(RI1H ~ GroupGenotypetime, data=data) anova(model)
library(emmeans) marginal = emmeans(model,pairwise ~ Group,adjust=“tukey”)
marginal = emmeans(model,pairwise ~ group:genotype,adjust=“tukey”)
marginal = emmeans(model,pairwise ~ Group:time,adjust=“tukey”) marginal = emmeans(model,pairwise ~ Genotype,adjust=“tukey”) marginal = emmeans(model,pairwise ~ time,adjust=“tukey”) ### Tukey-adjusted comparisons marginal$contrasts
library(ggplot2) p = ggplot(data=data, aes(x=TimexGenotype, y=RI24H, fill=Group), color=NA) p = p + stat_summary(fun.y = mean, geom = “bar”, position = “dodge”) + stat_summary(fun.data = mean_cl_normal,geom = “errorbar”,position = position_dodge(width = 0.9),width = 0.2) p = p + labs(title=“NORT-Final Data-20s”)+ylab(“RI-24H”)+xlab(“”)+ scale_x_discrete(name=“TimexGenotype”) p= p + scale_fill_grey() + theme_classic() p p = ggplot(data=data, aes(x=TimexGenotype, y=RI1H, fill=Group), color=NA) p = p + stat_summary(fun.y = mean, geom = “bar”, position = “dodge”) + stat_summary(fun.data = mean_cl_normal,geom = “errorbar”,position = position_dodge(width = 0.9),width = 0.2) p = p + labs(title=“NORT-Final Data-20s”)+ylab(“RI-1H”)+xlab(“”)+ scale_x_discrete(name=“TimexGenotype”) p= p + scale_fill_grey() + theme_classic() p