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}}
lsmeans
3 messages · Nutter, Benjamin, Frank E Harrell Jr, John Fox
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 Benjamin
As 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
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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}}
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