【求助】Binary response 的 GLM 问题

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The data here are concerned with whether people default on a loan taken from a particular bank and for identical interest rates and for a fixed period. The information on each individual is their sex (male of female); their income (in pounds), whether the person is a home owner or not, their age (in years), and the amount of the loan (in pounds).

The information recorded is whether the individal defaulted on the loan or not. Study the data and try and understand a relation between the persons characteristics and defaulting. Specifically, what is your estimated probability that a female aged 42, who is not a home owner, has an income of 23,500, and took a loan of 12,000, defaults on the loan?

The table holding the data have headings as follows:

m/f: male=1, female=0
age: age in years
home: home=1 is a home owner, home=0 is not a home owner
inc: income
loan: amount of loan
def: default=1, non-default=0.

1. Q3=read.table("tabl3.txt")
   
2. colnames(Q3)=c("Sex","Age","Home","Inc","Loan","Def")
   
3. Q3$Sex=as.factor(Q3$Sex)
   
4. Q3$Home=as.factor(Q3$Home)
   
5. Q3$Def=as.factor(Q3$Def)
   
6. summary(Q3)

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然后用glm分析response.

1. Q3.mod=glm(Def~Sex+Age+Home+Inc+Loan,family=binomial)

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总感觉不对，好像不是这样的。response 好像不应该用Def。一下子卡在那里了。。

希望各位提供点意见。

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关键词：response Binary resp bin esp Binary response GLM

亲，不是这个样子滴～

这个和研究的目的相关.

先要明确研究的目的，再寻找合适的方法用来建模。

而不是先想好用哪种方法来凑模型