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模型中存在错误。框架默认值(Terms,newdata,na.action=na.action,xlev=object$xlevels):因子X有新的级别

logistic-regression r

Hadsga · 技术社区 · 7 年前

 EW <- glm(everwrk~age_p + r_maritl, data = NH11, family = "binomial")

此外,我想预测 everwrk r_maritl

r\u maritl

levels(NH11$r_maritl)
 "0 Under 14 years" 
 "1 Married - spouse in household" 
 "2 Married - spouse not in household"
 "3 Married - spouse in household unknown" 
 "4 Widowed"                               
 "5 Divorced"                             
 "6 Separated"                             
 "7 Never married"                        
 "8 Living with partner"  
 "9 Unknown marital status"

predEW <- with(NH11,
expand.grid(r_maritl = c( "0 Under 14 years", "1 Married - 
spouse in household", "2 Married - spouse not in household", "3 Married - 
spouse in household unknown", "4 Widowed", "5 Divorced", "6 Separated", "7 
Never married", "8 Living with partner", "9 Unknown marital status"),
age_p = mean(age_p,na.rm = TRUE)))

cbind(predEW, predict(EW, type = "response",
                        se.fit = TRUE, interval = "confidence",
                        newdata = predEW))

问题是我得到了以下回应:

-未知家庭中的配偶

str(NH11$age_p)
num [1:33014] 47 18 79 51 43 41 21 20 33 56 ...

str(NH11$everwrk)
Factor w/ 2 levels "2 No","1 Yes": NA NA 2 NA NA NA NA NA 2 2 ...

str(NH11$r_maritl)
Factor w/ 10 levels "0 Under 14 years",..: 6 8 5 7 2 2 8 8 8 2 ...

2 回复 | 直到 7 年前

Ben Bolker 7 年前

tl;博士 看起来您的因子中有一些级别没有在数据中表示,这些级别是从模型中使用的因子中删除的。事后看来,这并不奇怪,因为你无法预测这些水平的反应。也就是说 轻微地 NA 自动设置值。您可以使用 levels(droplevels(NH11$r_maritl)) 在构建预测框架时,或等效地 EW$xlevels$r_maritl

可复制示例:

maritl_levels <- c( "0 Under 14 years", "1 Married - spouse in household", 
  "2 Married - spouse not in household", "3 Married - spouse in household unknown", 
  "4 Widowed", "5 Divorced", "6 Separated", "7 Never married", "8 Living with partner", 
 "9 Unknown marital status")
set.seed(101)
NH11 <- data.frame(everwrk=rbinom(1000,size=1,prob=0.5),
                 age_p=runif(1000,20,50),
                 r_maritl = sample(maritl_levels,size=1000,replace=TRUE))

让我们做一个缺失的级别:

NH11 <- subset(NH11,as.numeric(NH11$r_maritl) != 3)

EW <- glm(everwrk~r_maritl+age_p,data=NH11,family=binomial)
predEW <- with(NH11,
  expand.grid(r_maritl=levels(r_maritl),age_p=mean(age_p,na.rm=TRUE)))
predict(EW,newdata=predEW)

模型中存在错误。框架默认值(Terms,newdata,na.action=na.action,xlev=object$xlevels):

predEW <- with(NH11,
           expand.grid(r_maritl=EW$xlevels$r_maritl,age_p=mean(age_p,na.rm=TRUE)))
predict(EW,newdata=predEW)

Nad Pat 3 年前

非常感谢你的回答,我也面临着同样的问题,新的水平。

我正在使用 data.frame() expand.grid() 作用
na.rm=TRUE 以及均值函数中的变量
glmoutput$xlevels$variablename

而且解决方案有效!