我已经阅读了我的.CSV，然后使用多种方法将文件转换为数据框，包括：
df<-read.csv('cdSH2015Fall.csv', dec = ".", na.strings = c("na"), header=TRUE,
row.names=NULL, stringsAsFactors=F)
df<-as.data.frame(lapply(df, unlist)) # converted .csv to a a data.frame
str(df) # provides the structure of df.
'data.frame': 72 obs. of 16 variables:
$ trtGroup : Factor w/ 68 levels "AANN","AAPN",..: 5 7 14 18 20 23
27 33 37 48 ...
$ cd : Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 1 ...
$ PreviousExp : Factor w/ 2 levels "Empty","Enriched": 2 1 2 2 2 2 1
1 1 1 ...
$ treatment : Factor w/ 2 levels "NN","PN": 1 1 1 1 1 1 1 1 1 1 ...
$ total.Area.DarkBlue.: num 827 1037 663 389 983 ...
$ numberOfGroups : int 1 1 1 1 1 1 1 1 1 1 ...
$ totalGroupArea : num 15.72 2.26 9.45 11.57 9.73 ...
$ averageGrpArea : num 15.72 2.26 9.45 11.57 9.73 ...
$ proximityToPlants : num 5.65 16.05 2.58 9.65 4.74 ...
$ latFeed : num 2 0.5 0 1 0 0 1 0.5 2 1 ...
$ latBalloon : num 6 2 2 NA 0 0.1 3 0.5 1 0.7 ...
$ countChases : int 5 8 16 4 16 21 18 11 14 28 ...
$ chases : int 95 87 67 923 636 96 1210 571 775 816 ...
$ grpDiameter : num 16.8 23.3 19.5 11.2 29.9 ...
$ grpActiv : num 4908 5164 4197 5263 5377 ...
$ NND : num 0 11.88 8.98 3.6 9.8 ...
然后我以两种方式运行我的模型：
第一个选项。
fit = t.test(df$proximityToPlants[which (df$cd==1 &
df$treatment == 'PN')], df$proximityToPlants[which
(df$cd==0 & df$treatment == 'PN')]
)
第二个选项试图确保我有一个合适的数据框。
子集数据然后创建矩阵。
cdProximityToPlantsPN<-cdSH2015Fall$proximityToPlants[which (cdSH2015Fall$cd==1 & cdSH2015Fall$treatment == 'PN')]
H2ProximityToPlantsPN<-cdSH2015Fall$proximityToPlants[which (cdSH2015Fall$cd==0 & cdSH2015Fall$treatment == 'PN')]
cdProximityToPlantsNN<-cdSH2015Fall$proximityToPlants[which (cdSH2015Fall$cd==1 & cdSH2015Fall$treatment == 'NN')]
H2ProximityToPlantsNN<-cdSH2015Fall$proximityToPlants[which (cdSH2015Fall$cd==0 & cdSH2015Fall$treatment == 'NN')]
创建矩阵
df<-
cbind(cdProximityToPlantsPN,H2ProximityToPlantsPN,cdProximityToPlantsNN,
H2ProximityToPlantsNN)
mat <- sapply(df,unlist)
fit=t.test(mat[,1],mat[,2], paired = F, var.equal = T)
然而，在使用以下内容评估异常值时，我仍然会遇到错误：
outlierTest(fit) # Bonferonni p-value for most extreme obs
Error in UseMethod("outlierTest") :
no applicable method for 'outlierTest' applied to an object of class
"htest"
qqPlot(fit, main="QQ Plot") #qq plot for studentized resid
Error in order(x[good]) : unimplemented type 'list' in 'orderVector1'
leveragePlots(fit) # leverage plots
Error in formula.default(model) : invalid formula
我知道问题必须与我的数据结构有关。关于如何解决它的任何想法？