[R] Bootstrapping confidence intervals
khosoda at med.kobe-u.ac.jp
khosoda at med.kobe-u.ac.jp
Tue May 3 08:40:11 CEST 2011
Hi,
Sorry for repeated question.
I performed logistic regression using lrm and penalized it with pentrace
function. I wanted to get confidence intervals of odds ratio of each
predictor and summary(MyModel) gave them. I also tried to get
bootstrapping standard errors in the logistic regression. bootcov
function in rms package provided them. Then, I found that the confidence
intervals provided by bootstrapping (bootcov) was narrower than CIs
provided by usual variance-covariance matrix in the followings.
My data has no cluster structure.
I am wondering which confidence interval is better. I guess
bootstrapping one, but is it right?
I would appreciate anybody's help in advance.
> summary(MyModel, stenosis=c(70, 80), x1=c(1.5, 2.0), x2=c(1.5, 2.0))
Effects Response : outcome
Factor Low High Diff. Effect S.E. Lower 0.95 Upper 0.95
stenosis 70.0 80 10.0 -0.11 0.24 -0.59 0.37
Odds Ratio 70.0 80 10.0 0.90 NA 0.56 1.45
x1 1.5 2 0.5 1.21 0.37 0.49 1.94
Odds Ratio 1.5 2 0.5 3.36 NA 1.63 6.95
x2 1.5 2 0.5 -0.29 0.19 -0.65 0.08
Odds Ratio 1.5 2 0.5 0.75 NA 0.52 1.08
ClinicalScore 3.0 5 2.0 0.61 0.38 -0.14 1.36
Odds Ratio 3.0 5 2.0 1.84 NA 0.87 3.89
procedure - CA:CE 2.0 1 NA 0.83 0.46 -0.07 1.72
Odds Ratio 2.0 1 NA 2.28 NA 0.93 5.59
> summary(MyModel.boot, stenosis=c(70, 80), x1=c(1.5, 2.0), x2=c(1.5, 2.0))
Effects Response : outcome
Factor Low High Diff. Effect S.E. Lower 0.95 Upper 0.95
stenosis 70.0 80 10.0 -0.11 0.28 -0.65 0.43
Odds Ratio 70.0 80 10.0 0.90 NA 0.52 1.54
x1 1.5 2 0.5 1.21 0.29 0.65 1.77
Odds Ratio 1.5 2 0.5 3.36 NA 1.92 5.89
x2 1.5 2 0.5 -0.29 0.16 -0.59 0.02
Odds Ratio 1.5 2 0.5 0.75 NA 0.55 1.02
ClinicalScore 3.0 5 2.0 0.61 0.45 -0.28 1.50
Odds Ratio 3.0 5 2.0 1.84 NA 0.76 4.47
procedure - CAS:CEA 2.0 1 NA 0.83 0.38 0.07 1.58
Odds Ratio 2.0 1 NA 2.28 NA 1.08 4.85
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