Re: [R] Marginal Effect larger than 1 for a binary variable (summary.Design after lrm)

From: Minyu Chen <minyu.chen_at_ucl.ac.uk>
Date: Fri 27 Oct 2006 - 16:57:49 GMT

On Oct 27, 2006, at 5:54 PM, Minyu Chen wrote:

> Dear All:
>
> I run a logistic regression (using lrm in the Design package), and
> after that, I use the command "summary" to get the marginal effects
> of each variable. But one strange thing happens on my binary
> dependent variable: The marginal effect of it jumping from 0 to 1
> is 1.77. I believe the marginal effect of binary variable x1 has
> interpretation should be P(Y=1|x1=1, x2...)-P(Y=1|x1=0,x2...). As
> both terms lies in [0,1], their difference shouldn't be larger than 1.
>
> Besides this, I also get some boundary number for the marginal
> effect of the same binary variable (in datasets of other years)
> like .98, .97, with which I am not comfortable either. I suspect I
> did something wrong.
>
> This is part of my model:
>
> > resultt1
>
> Logistic Regression Model
>
> lrm(formula = typemort ~ adv_binc_ratio + agem1 + regEA + regEM +
> regGL + regN + regNI + regNW + regS + regSW + regW + regWM +
> regY + repmethIO + repmethSR + no_dis_no_def + prevLO + prevOO +
> prevRP + owning + adv_binc_ratio * (repmethIO + repmethSR +
> no_dis_no_def + prevLO + prevOO + prevRP + owning) + agem1 *
> (repmethIO + repmethSR + no_dis_no_def + prevLO + prevOO +
> prevRP + owning), data = a)
>
>
> This is part of my result:
>
> > summary(resultt1,adv_binc_ratio=mean(a$adv_binc_ratio),agem1=mean
> (a$agem1),repmethIO=c(0,mean(a$repmethIO),1),repmethSR=c(0,mean(a
> $repmethSR),1),no_dis_no_def=c(0,mean(a$no_dis_no_def),1),prevLO=c
> (0,mean(a$prevLO),1),prevOO=c(0,mean(a$prevOO),1),prevRP=c(0,mean(a
> $prevRP),1),regEA=c(0,mean(a$regEA),1),regEM=mean(a
> $regEM),regGL=mean(a$regGL),regN=mean(a$regN),regNI=mean(a
> $regNI),regNW=mean(a$regNW),regS=mean(a$regS),regSW=mean(a
> $regSW),regW=mean(a$regW),regWM=mean(a$regWM),regY=mean(a
> $regY),owning=c(0,mean(a$owning),1))
> Effects Response : typemort
>
> Factor Low High Diff. Effect S.E. Lower 0.95 Upper
> 0.95
> no_dis_no_def 0.0000 1.0000 1.0000 1.76 0.03 1.69 1.82
> Odds Ratio 0.0000 1.0000 1.0000 5.79 NA 5.41 6.19
>
> Adjusted to: adv_binc_ratio=2.611027 agem1=40.47638
> repmethIO=0.1456293 repmethSR=0.6711471 no_dis_no_def=0.4463533
> prevLO=0.06590113 prevOO=0.7785591 prevRP=0.06738472 owning=0.4765593
>
> Thank you very much for your help.
>
> Thanks,
> Minyu Chen
>



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