R-将字符串值从列表中应用于默认的DRC函数

Question

我正在运行多种模型和功能。我需要将列表中的值应用于默认的r函数，例如modelfit((我的想法是将相同的函数运行到多种模型，并在。

之后编译结果。

我正在尝试使用循环和R中的"应用"功能的家族，但没有成功。

#package drc is necessary
library(drc)
#my data
rates <- c(.1,.1,.1,1,1,1,10,10,10,100,100,100,1000,1000,1000,.1,.1,.1,1,1,1,10,10,10,100,100,100,1000,1000,1000)
prod <- c("A","A","A","A","A","A","A","A","A","A","A","A","A","A","A","B","B","B","B","B","B","B","B","B","B","B","B","B","B","B")
resp <- c(.295,.32,.301,.155,.1501,.148,.05,.03,.044,.002,.001,.0015,.001,.0005,.0003,.312,.337,.299,.265,.2501,.248,.102,.103,.114,.02,.01,.015,.003,.0002,.0007)
data.test <- data.frame(rates,prod,resp) #my data frame
#my models
m1 <- drm(resp~rates, fct=LL.4(), data=data.test[data.test$prod=="A",])
m2 <- drm(resp~rates, fct=LL.4(), data=data.test[data.test$prod=="B",])
#lack of fit test
modelFit(m1)
modelFit(m2)
#I can get the modelFit p-values this way:
modelFit(m1)$"p value"[2]
modelFit(m2)$"p value"[2]

#I have several models. I want to create a loop to give me only the p value for each model fit. I want to use that for other information given by the summaries and function
#list of models
modelsList <- c("m1","m2")
#I can print the strings with the loop
for(i in modelsList){
  print(i)
  }

我的想法是使用字符串添加默认" DRC"函数Modelfit((的信息。结果将是一个列表，其中循环中所有结果中的所有P值都有一个列表，但是我遇到了错误：

错误：$运算符对原子向量无效

#Not working
for(i in modelsList){
  modelFit(i)$"p value"[2]
  }
#Error
# Error: $ operator is invalid for atomic vectors
#Trying to use lapply
#Following this logic
lapply(modelsList, function(x) print(x))
#I could not get the results
lapply(modelsList, function(x) modelFit(x)$"p value"[2])

通过结果，我将继续并创建一个数据。

很高兴见到你，danilo

我认为您错过了drm功能。

modelsList <- c("m1","m2")
prod = c("A","B")
type = data.frame(modelsList,
                  prod)
#I can print the strings with the loop
for(i in modelsList){
  print(i)
}

for(i in modelsList){
  model_Prod = type[modelsList == i,]$prod
  drm_result<-drm(resp~rates, fct=LL.4(), data=data.test[data.test$prod==model_Prod,])
  print(modelFit(drm_result)$"p value"[2])
}
# lapply
lapply(modelsList, function(x) {
  model_Prod = type[modelsList == x,]$prod
  x<-drm(resp~rates, fct=LL.4(), data=data.test[data.test$prod==model_Prod,])
  modelFit(x)$"p value"[2]
}
)

继续，在史蒂夫·李输入之后，我可以生成一个数据。

#source of information:
#https://stackoverflow.com/questions/25285570/invalid-factor-level-with-rbind-to-data-frame
#df.results will be a data.frane with headers = "Model" and "ModelFit_pvalue""
df.results <- NULL
#Loop to print only specif information requested from function and add it to a data frame
for(i in modelsList){
  model_Prod = type[modelsList == i,]$prod
  drm_result<-drm(resp~rates, fct=LL.4(), data=data.test[data.test$prod==model_Prod,])
  #print(i)
  #print(modelFit(drm_result)$"p value"[2])
  modelpvalue <- modelFit(drm_result)$"p value"[2] #store p values in a variable
  de <- data.frame("Model"=i,"ModelFit_pvalue"= modelpvalue)
  df.results = rbind(df.results,de)
}
df.results
#df.results output:
  Model ModelFit_pvalue
1    m1       0.2346460
2    m2       0.5757368