Hi all!
I've got this error while running
example(Glm)
library("rms")
> example(Glm)
Glm> ## Dobson (1990) Page 93: Randomized Controlled Trial :
Glm> counts <- c(18,17,15,20,10,20,25,13,12)
Glm> outcome <- gl(3,1,9)
Glm> treatment <- gl(3,3)
Glm> f <- glm(counts ~ outcome + treatment, family=poisson())
Glm> f
Call: glm(formula = counts ~ outcome + treatment, family = poisson())
Coefficients:
(Intercept) outcome2 outcome3 treatment2 treatment3
3.045e+00 -4.543e-01 -2.930e-01 -4.210e-16 -3.997e-16
Degrees of Freedom: 8 Total (i.e. Null); 4 Residual
Null Deviance: 10.58
Residual Deviance: 5.129 AIC: 56.76
Glm> anova(f)
Analysis of Deviance Table
Model: poisson, link: log
Response: counts
Terms added sequentially (first to last)
Df Deviance Resid. Df Resid. Dev
NULL 8 10.5814
outcome 2 5.4523 6 5.1291
treatment 2 0.0000 4 5.1291
Glm> summary(f)
Call:
glm(formula = counts ~ outcome + treatment, family = poisson())
Deviance Residuals:
1 2 3 4 5 6 7 8
-0.67125 0.96272 -0.16965 -0.21999 -0.95552 1.04939 0.84715 -0.09167
9
-0.96656
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.045e+00 1.709e-01 17.815 <2e-16 ***
outcome2 -4.543e-01 2.022e-01 -2.247 0.0246 *
outcome3 -2.930e-01 1.927e-01 -1.520 0.1285
treatment2 -4.210e-16 2.000e-01 0.000 1.0000
treatment3 -3.997e-16 2.000e-01 0.000 1.0000
---
Signif. codes: 0 â***â 0.001 â**â 0.01 â*â 0.05 â.â 0.1 â
â 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 10.5814 on 8 degrees of freedom
Residual deviance: 5.1291 on 4 degrees of freedom
AIC: 56.761
Number of Fisher Scoring iterations: 4
Glm> f <- Glm(counts ~ outcome + treatment, family=poisson())
Error in Design(eval(mf, parent.frame())) :
dataset dd not found for options(datadist=)
My session Info
sessionInfo()
R version 2.12.1 Patched (2011-01-08 r53945)
Platform: x86_64-unknown-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=C LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] tcltk tools splines stats graphics grDevices utils
[8] datasets methods base
other attached packages:
[1] lattice_0.19-17 debug_1.2.4 mvbutils_2.5.4 rms_3.1-0
[5] mgcv_1.7-2 Hmisc_3.8-3 survival_2.36-2 foreign_0.8-41
loaded via a namespace (and not attached):
[1] cluster_1.13.2 grid_2.12.1 Matrix_0.999375-46 nlme_3.1-97
While I don't have this issue on another R-machine
> library(rms)
> example(Glm)
Glm> ## Dobson (1990) Page 93: Randomized Controlled Trial :
Glm> counts <- c(18,17,15,20,10,20,25,13,12)
Glm> outcome <- gl(3,1,9)
Glm> treatment <- gl(3,3)
Glm> f <- glm(counts ~ outcome + treatment, family=poisson())
Glm> f
Call: glm(formula = counts ~ outcome + treatment, family = poisson())
Coefficients:
(Intercept) outcome2 outcome3 treatment2 treatment3
3.045e+00 -4.543e-01 -2.930e-01 8.717e-16 4.557e-16
Degrees of Freedom: 8 Total (i.e. Null); 4 Residual
Null Deviance: 10.58
Residual Deviance: 5.129 AIC: 56.76
Glm> anova(f)
Analysis of Deviance Table
Model: poisson, link: log
Response: counts
Terms added sequentially (first to last)
Df Deviance Resid. Df Resid. Dev
NULL 8 10.5814
outcome 2 5.4523 6 5.1291
treatment 2 0.0000 4 5.1291
Glm> summary(f)
Call:
glm(formula = counts ~ outcome + treatment, family = poisson())
Deviance Residuals:
1 2 3 4 5 6 7 8
-0.67125 0.96272 -0.16965 -0.21999 -0.95552 1.04939 0.84715 -0.09167
9
-0.96656
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.045e+00 1.709e-01 17.815 <2e-16 ***
outcome2 -4.543e-01 2.022e-01 -2.247 0.0246 *
outcome3 -2.930e-01 1.927e-01 -1.520 0.1285
treatment2 8.717e-16 2.000e-01 0.000 1.0000
treatment3 4.557e-16 2.000e-01 0.000 1.0000
---
Signif. codes: 0 â***â 0.001 â**â 0.01 â*â 0.05 â.â 0.1 â
â 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 10.5814 on 8 degrees of freedom
Residual deviance: 5.1291 on 4 degrees of freedom
AIC: 56.761
Number of Fisher Scoring iterations: 4
Glm> f <- Glm(counts ~ outcome + treatment, family=poisson())
Glm> # could have had rcs( ) etc. if there were continuous predictors
Glm> f
General Linear Model
Glm(formula = counts ~ outcome + treatment, family = poisson())
Model Likelihood
Ratio Test
Obs 9 LR chi2 5.45
Residual d.f. 4 d.f. 4
g 0.227 Pr(> chi2) 0.2440
Coef S.E. Wald Z Pr(>|Z|)
Intercept 3.0445 0.1709 17.81 <0.0001
outcome2 -0.4543 0.2022 -2.25 0.0246
outcome3 -0.2930 0.1927 -1.52 0.1285
treatment2 0.0000 0.2000 0.00 1.0000
treatment3 0.0000 0.2000 0.00 1.0000
Glm> anova(f)
Wald Statistics Response: counts
Factor Chi-Square d.f. P
outcome 5.49 2 0.0643
treatment 0.00 2 1.0000
TOTAL 5.49 4 0.2409
Glm> summary(f, outcome=c('1','2','3'), treatment=c('1','2','3'))
Effects Response : counts
Factor Low High Diff. Effect S.E. Lower 0.95 Upper 0.95
outcome - 1:2 2 1 NA 0.45 0.20 0.06 0.85
outcome - 3:2 2 3 NA 0.16 0.22 -0.26 0.58
treatment - 1:2 2 1 NA 0.00 0.20 -0.39 0.39
treatment - 3:2 2 3 NA 0.00 0.20 -0.39 0.39
> sessionInfo()
R version 2.12.1 (2010-12-16)
Platform: i686-pc-linux-gnu (32-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=C LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] splines stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] rms_3.1-0 Hmisc_3.8-3 survival_2.36-2
loaded via a namespace (and not attached):
[1] cluster_1.13.2 grid_2.12.1 lattice_0.19-13 tools_2.12.1
Many thanks
Anna
Anna Freni Sterrantino
Ph.D Student
Department of Statistics
University of Bologna, Italy
via Belle Arti 41, 40124 BO.
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