> On Sep 14, 2017, at 12:30 AM, Bonnett, Laura <l.j.bonn...@liverpool.ac.uk>
> wrote:
>
> Dear all,
>
> I am using the publically available GustoW dataset. The exact version I am
> using is available here:
> https://drive.google.com/open?id=0B4oZ2TQA0PAoUm85UzBFNjZ0Ulk
>
> I would like to produce a nomogram for 5 covariates - AGE, HYP, KILLIP, HRT
> and ANT. I have successfully fitted a logistic regression model using the
> "glm" function as shown below.
>
> library(rms)
> gusto <- spss.get("GustoW.sav")
> fit <-
> glm(DAY30~AGE+HYP+factor(KILLIP)+HRT+ANT,family=binomial(link="logit"),data=gusto,x=TRUE,y=TRUE)
>
> However, my review of the literature and other websites suggest I need to use
> "lrm" for the purposes of producing a nomogram. When I run the command using
> "lrm" (see below) I get an error message saying:
> Error in lrm(DAY30 ~ AGE + HYP + KILLIP + HRT + ANT, gusto2) :
> Unable to fit model using "lrm.fit"
>
> My code is as follows:
> gusto2 <- gusto[,c(1,3,5,8,9,10)]
> gusto2$HYP <- factor(gusto2$HYP, labels=c("No","Yes"))
> gusto2$KILLIP <- factor(gusto2$KILLIP, labels=c("1","2","3","4"))
> gusto2$HRT <- factor(gusto2$HRT, labels=c("No","Yes"))
> gusto2$ANT <- factor(gusto2$ANT, labels=c("No","Yes"))
> var.labels=c(DAY30="30-day Mortality", AGE="Age in Years", KILLIP="Killip
> Class", HYP="Hypertension", HRT="Tachycardia", ANT="Anterior Infarct
> Location")
> label(gusto2)=lapply(names(var.labels),function(x)
> label(gusto2[,x])=var.labels[x])
>
> ddist = datadist(gusto2)
> options(datadist='ddist')
>
> fit1 <- lrm(DAY30~AGE+HYP+KILLIP+HRT+ANT,gusto2)
>
> Error in lrm(DAY30 ~ AGE + HYP + KILLIP + HRT + ANT, gusto2) :
> Unable to fit model using "lrm.fit"
>
> Online solutions to this problem involve checking whether any variables are
> redundant. However, the results for my data suggest that none are.
> redun(~AGE+HYP+KILLIP+HRT+ANT,gusto2)
>
> Redundancy Analysis
>
> redun(formula = ~AGE + HYP + KILLIP + HRT + ANT, data = gusto2)
>
> n: 2188 p: 5 nk: 3
>
> Number of NAs: 0
>
> Transformation of target variables forced to be linear
>
> R-squared cutoff: 0.9 Type: ordinary
>
> R^2 with which each variable can be predicted from all other variables:
>
> AGE HYP KILLIP HRT ANT
> 0.028 0.032 0.053 0.046 0.040
>
> No redundant variables
>
> I've also tried just considering "lrm.fit" and that code seems to run without
> error too:
> lrm.fit(cbind(gusto2$AGE,gusto2$KILLIP,gusto2$HYP,gusto2$HRT,gusto2$ANT),gusto2$DAY30)
>
> Logistic Regression Model
>
> lrm.fit(x = cbind(gusto2$AGE, gusto2$KILLIP, gusto2$HYP, gusto2$HRT,
> gusto2$ANT), y = gusto2$DAY30)
>
> Model Likelihood Discrimination Rank Discrim.
> Ratio Test Indexes Indexes
> Obs 2188 LR chi2 233.59 R2 0.273 C 0.846
> 0 2053 d.f. 5 g 1.642 Dxy 0.691
> 1 135 Pr(> chi2) <0.0001 gr 5.165 gamma 0.696
> max |deriv| 4e-09 gp 0.079 tau-a 0.080
> Brier 0.048
>
> Coef S.E. Wald Z Pr(>|Z|)
> Intercept -13.8515 0.9694 -14.29 <0.0001
> x[1] 0.0989 0.0103 9.58 <0.0001
> x[2] 0.9030 0.1510 5.98 <0.0001
> x[3] 1.3576 0.2570 5.28 <0.0001
> x[4] 0.6884 0.2034 3.38 0.0007
> x[5] 0.6327 0.2003 3.16 0.0016
>
> I was therefore hoping someone would explain why the "lrm" code is producing
> an error message, while "lrm.fit" and "glm" do not. In particular I would
> welcome a solution to ensure I can produce a nomogram.
Try this:
lrm # look at code, do a search on "fail"
?lrm.fit # read the structure of the returned value of lrm.fit
my.fit <- lrm.fit(x = cbind(gusto2$AGE, gusto2$KILLIP, gusto2$HYP, gusto2$HRT,
gusto2$ANT), y = gusto2$DAY30)
print(my.fit$fail) # the error message you got from the lrm call means
convergence failed
Documentation bug: The documentation of the cause of the 'fail'- value
incorrectly gives the name of this parameter as 'maxiter' in the Value section.
--
David.
>
> Kind regards,
> Laura
>
> Dr Laura Bonnett
> NIHR Post-Doctoral Fellow
>
> Department of Biostatistics,
> Waterhouse Building, Block F,
> 1-5 Brownlow Street,
> University of Liverpool,
> Liverpool,
> L69 3GL
>
> 0151 795 9686
> l.j.bonn...@liverpool.ac.uk
>
>
>
> [[alternative HTML version deleted]]
>
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David Winsemius
Alameda, CA, USA
'Any technology distinguishable from magic is insufficiently advanced.'
-Gehm's Corollary to Clarke's Third Law
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