R help - Oct 2010 - Extract summary stats to table

Dear List,

I am looking to run a host of models (60) with three methods - lmer,glm and lrm.

Is there a way to output the key stats into a table that i can copy to excel?

I.e for lmer i would want AIC,BIC etc
     for lrm i would want Brier score, r2, c-value etc

At present i am running the models from a script and then copying across the
values into a excel spreadsheet however this is time consuming and i imagine
their must be a trick?

Thanks

Chris

Dear List,

I am looking to run a host of models (60) with three methods - lmer,glm and lrm.

Is there a way to output the key stats into a table that i can copy to excel?

I.e for lmer i would want AIC,BIC etc
    for lrm i would want Brier score, r2, c-value etc

At present i am running the models from a script and then copying across the
values into a excel spreadsheet however this is time consuming and i imagine
their must be a trick?

I had thought of setting up a data frame and populating it with the scores but i
am not very experienced and am unsure of how to do it?

Thanks

Chris

Hi

r-help-bounces at r-project.org napsal dne 05.10.2010 13:46:49:
> 
> Dear List,
> 
> I am looking to run a host of models (60) with three methods - lmer,glm 
and lrm.
> 
> Is there a way to output the key stats into a table that i can copy to 
excel?
> 
> I.e for lmer i would want AIC,BIC etc
>     for lrm i would want Brier score, r2, c-value etc
> 
> At present i am running the models from a script and then copying across 
the 
> values into a excel spreadsheet however this is time consuming and i 
imagine 
> their must be a trick?
> 
> I had thought of setting up a data frame and populating it with the 
scores but
> i am not very experienced and am unsure of how to do it?
If you do not wont set up data frame you can use write table to already 
existing file with append=TRUE option

write.table(some.data, "result.xls", sep = "\t", row.names =
F, append=T)

where some.data is matrix with one row and desired number of columns.

I presume the output is numeric.

Regards
Petr

> 
> Thanks
> 
> Chris
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide 
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

Write a function that does your analysis and returns the values of interest in a
vector.  Then run the function multiple times using replicate or sapply and the
results will be put into a matrix for you.

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Chris Mcowen
> Sent: Tuesday, October 05, 2010 5:47 AM
> To: r-help at r-project.org
> Subject: [R] Extract summary stats to table
> 
> 
> Dear List,
> 
> I am looking to run a host of models (60) with three methods - lmer,glm
> and lrm.
> 
> Is there a way to output the key stats into a table that i can copy to
> excel?
> 
> I.e for lmer i would want AIC,BIC etc
>     for lrm i would want Brier score, r2, c-value etc
> 
> At present i am running the models from a script and then copying
> across the values into a excel spreadsheet however this is time
> consuming and i imagine their must be a trick?
> 
> I had thought of setting up a data frame and populating it with the
> scores but i am not very experienced and am unsure of how to do it?
> 
> Thanks
> 
> Chris
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.

Chris,

Here is an example.  Please ignore the particulars of the models - they were
built only to demonstrate sapply():


library(lme4)

statedata <- data.frame(state.x77, state.region)

#create empty list object
mods <- list()

#run the models, adding each one to the list
mods$m1 <- glm(Income ~ Life.Exp, data=statedata, family
gaussian(link="log"))
mods$m2 <- update(mods$m1, . ~ . + HS.Grad)
mods$m3 <- update(mods$m2, . ~ . + Population)
mods$m4 <- lmer(Income ~ Life.Exp + (1|state.region), data=statedata)

#collect the model fit info with sapply() and store as data frame
dfmi <- data.frame(
  Formula=sapply(mods, FUN=function(x){ paste(formula(x)[2], formula(x)[1],
formula(x)[-c(1,2)], collapse=" ") } ),
  AIC=sapply(mods, FUN="AIC") )

#write the data frame to a comma-separated file
write.table(dfmi, file="dfmi.txt", col.names=TRUE, sep=",")

Nathan Pellegrin

	[[alternative HTML version deleted]]