显然这段代码可以解决问题:
result_anova<-data.frame()
for (i in 1:length(levels(data$a))){
levels<-levels(data$a)
assign(paste("data_", levels[i], sep = ""), subset(data, a==levels[i]))
result<-as.data.frame(anova(lm(var~b, subset(data, a==levels[i]))))
result_anova[i, 1]<-levels[i]
result_anova[i, 2]<-result[1, 1 ]
result_anova[i, 3]<-result[1, 2 ]
result_anova[i, 4]<-result[1, 3 ]
result_anova[i, 5]<-result[1, 4 ]
result_anova[i, 6]<-result[1, 5 ]
result_anova[i, 7]<-result[2, 1 ]
result_anova[i, 8]<-result[2, 2 ]
result_anova[i, 9]<-result[2, 3 ]
result_anova[i, 10]<-result[2, 4 ]
result_anova[i, 11]<-result[2, 5 ]
colnames(result_anova_genos)<-c ( "genotype", "Df_fac", "Sum_Sq_fac", "Mean_Sq_fac", "F_value_fac", "Pr(>F)_fac", "Df_res", "Sum_Sq_res", "Mean_Sq_res", "F_value_res", "Pr(>F)_res")
}
请对此答案投票或让我知道此代码是否可以改进。