Question: 95%CI for Rsquared in linear regression
gravatar for toyan.j.p
4.4 years ago by
United States
toyan.j.p30 wrote:


I used SPSS to check R squared for associated SNPs in a model with sex and age as covariates and R squared change from step wise regression to find individual contribution of  other SNPs on the most prominent SNP by removing each of the associated SNPs.My query is that is it possible to compute 95% CI of R squared/R squared change obtained through linear regression of SNPs with a quantitative trait, if yes how?

thanks in advance for any help



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ADD COMMENTlink modified 4.4 years ago • written 4.4 years ago by toyan.j.p30

Thank you very much Sean for your help. I tried bootstrapping from in R,

However there are types of confidence interval returned there are options from "norm", "basic", "stud", "perc", "bca" and "all". Though they describe bca for R-squared for their mt cars data. Which type is to be reported since my original R-squared were got through SPSS with Sex and Age as covariates. There is no option here to give covariates.

thanks for the reply

ADD REPLYlink modified 5 months ago by RamRS27k • written 4.4 years ago by toyan.j.p30
gravatar for Sean Davis
4.4 years ago by
Sean Davis26k
National Institutes of Health, Bethesda, MD
Sean Davis26k wrote:

Getting CI for nearly any statistic of interest can often be accomplished using bootstrapping. Bootstrapping conditions in a complicated experimental design can be challenging to get right, though.

You may be better served by using penalized regression methods such as lasso or elasticnet which are designed to deal with the problem you describe in a formalized way.

ADD COMMENTlink modified 5 months ago by RamRS27k • written 4.4 years ago by Sean Davis26k
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