**From:** Thomas Lumley (*tlumley@u.washington.edu*)

**Date:** Wed 05 May 2004 - 00:12:36 EST

**Next message:**Thomas Lumley: "Re: [R] RE: more on lm(y~x) question: removing NA´s"**Previous message:**Liaw, Andy: "[R] RE: more on lm(y~x) question: removing NA´s"**In reply to:**Francis Dimzon: "[R] Epidemiology Tools"

Message-id: <Pine.A41.4.58.0405040652360.64916@homer34.u.washington.edu>

On Mon, 3 May 2004, Francis Dimzon wrote:

*> Hi all,
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*>
*

*> Please help on this. We will be teaching epidemiology using opensource
*

*> software. What are R built-in functions or functions in available packages
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*> that are capable of doing these:
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*>
*

*> a) Logistic regression (glm?)
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glm

*> b) Conditional logistic regression
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clogit (survival package)

*> c) Logistic regression with random effects
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It depends what you mean. Random intercept models are in the glmmML

package, approximate maximum likelihood for more complicated models (PQL) is

available in MASS and nlme packages. Doug Bates is making progress on

more accurate approximations, but I'm not sure where he's got to.

Personally, I teach marginal models (GEE estimates) before random

effects effects models to epidemiologists. GEE is in the gee and geepack

packages. (I realise this is a minority view, but it is based on

experience).

*> d) Beta-binomial regression
*

Don't know. I'd use a logistic regression model with sandwich variances

(eg gee or glm with robcov from the Design package). I don't see any real

advantage of beta-binomial regression.

*> e) Poisson regression
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glm

*> f) Weibull regression
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survreg in the survival package

*> g) Exponential regression
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For censored data, survreg, for uncensored data, glm

*> h) Cox proportional hazards regression
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coxph in survival

*> i) Cox regression with time repeated covariables
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coxph in survival

*> j) Kaplan-Meier Analysis and Plots
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survfit and survdiff (for left-truncated data you need to use coxph).

*> k) Post-fit analysis with plots, delta-betas, hazard functions
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Just about every model has delta-betas. For the Cox model look at the

help page help(residuals.coxph).

Tests and graphical diagnostics for the proportional hazards assumption

are in cox.zph. survfit() gives fitted survival curves

Hazard rate functions are estimated by the muhaz package.

*> l) meta analysis
*

rmeta (which is also useful for Mantel-Haenszel-type analyses of

stratified 2x2 tables, and for drawing forest plots even outside

meta-analyses).

-thomas

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**Next message:**Thomas Lumley: "Re: [R] RE: more on lm(y~x) question: removing NA´s"**Previous message:**Liaw, Andy: "[R] RE: more on lm(y~x) question: removing NA´s"**In reply to:**Francis Dimzon: "[R] Epidemiology Tools"

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