I hope you'll forgive me for resurrecting this thread. My question
refers to John Fox's comments in the discussion of lsmeans from
https://stat.ethz.ch/pipermail/r-help/2008-June/164106.html
John you said, "It wouldn't be hard, however, to do the computations
yourself, using the coefficient vector for the fixed effects and a
suitably constructed model-matrix to compute the effects; you could also
get standard errors by using the covariance matrix for the fixed
effects."
I've been able to make use of all of that except for the 'suitably
constructed model-matrix' part. I've looked through some other threads
on this topic, but am still a little in the dark as to what I'd need to
do to construct a suitable matrix.
I would like to use the least squares means to develop parameter
estimates for a parametric ROC analysis, as described by Mithat Gonen's
book (Analyzing Receiver Operating Characteristic Curves with SAS,
2007).
Any suggestions on references that would explain how to go about
constructing the suitable model matrix?
Many Thanks
Benjamin
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Visit us online at http://www.clevelandclinic.org for
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Nutter, Benjamin wrote:> I hope you'll forgive me for resurrecting this thread. My question > refers to John Fox's comments in the discussion of lsmeans from > https://stat.ethz.ch/pipermail/r-help/2008-June/164106.html > > John you said, "It wouldn't be hard, however, to do the computations > yourself, using the coefficient vector for the fixed effects and a > suitably constructed model-matrix to compute the effects; you could also > get standard errors by using the covariance matrix for the fixed > effects." > > I've been able to make use of all of that except for the 'suitably > constructed model-matrix' part. I've looked through some other threads > on this topic, but am still a little in the dark as to what I'd need to > do to construct a suitable matrix. > > I would like to use the least squares means to develop parameter > estimates for a parametric ROC analysis, as described by Mithat Gonen's > book (Analyzing Receiver Operating Characteristic Curves with SAS, > 2007). > > Any suggestions on references that would explain how to go about > constructing the suitable model matrix? > > Many Thanks > BenjaminAs an aside, what advantages does modeling an ROC curve have over doing direct covariate modeling of the response variable as usual? Frank -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University
Dear Benjamin, In the absence of interactions, a suitably constructed model matrix could, for example, allow one predictor to range over its values while others are held to typical values (such as means). The effects package does this for linear and generalized linear models (and soon for proportional-odds and multinomial-logit models), and produces reasonable displays when there are interactions and other complex terms (such as regression splines or polynomials) in a model, but it doesn't have methods for mixed-effects models or survival-regression models. I hope this helps, John ------------------------------ John Fox, Professor Department of Sociology McMaster University Hamilton, Ontario, Canada web: socserv.mcmaster.ca/jfox> -----Original Message----- > From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]On> Behalf Of Nutter, Benjamin > Sent: September-26-08 3:48 PM > To: r-help at r-project.org > Subject: Re: [R] lsmeans > > I hope you'll forgive me for resurrecting this thread. My question > refers to John Fox's comments in the discussion of lsmeans from > https://stat.ethz.ch/pipermail/r-help/2008-June/164106.html > > John you said, "It wouldn't be hard, however, to do the computations > yourself, using the coefficient vector for the fixed effects and a > suitably constructed model-matrix to compute the effects; you could also > get standard errors by using the covariance matrix for the fixed > effects." > > I've been able to make use of all of that except for the 'suitably > constructed model-matrix' part. I've looked through some other threads > on this topic, but am still a little in the dark as to what I'd need to > do to construct a suitable matrix. > > I would like to use the least squares means to develop parameter > estimates for a parametric ROC analysis, as described by Mithat Gonen's > book (Analyzing Receiver Operating Characteristic Curves with SAS, > 2007). > > Any suggestions on references that would explain how to go about > constructing the suitable model matrix? > > Many Thanks > Benjamin > > > P Please consider the environment before printing this e-mail > > Cleveland Clinic is ranked one of the top hospitals > in America by U.S. News & World Report (2008). > Visit us online at http://www.clevelandclinic.org for > a complete listing of our services, staff and > locations. > > > Confidentiality Note: This message is intended for use\...{{dropped:13}} > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.