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A simple command to grab coefficients, t-stats, p-values, f-stats, etc from a regression and export them as an easy to use spreadsheet.
lmOut <- function(res, file="test.csv", ndigit=3, writecsv=T) {
# If summary has not been run on the model then run summary
if (length(grep("summary", class(res)))==0) res <- summary(res)
co <- res$coefficients
nvar <- nrow(co)
ncol <- ncol(co)
f <- res$fstatistic
formatter <- function(x) format(round(x,ndigit),nsmall=ndigit)
# This sets the number of rows before we start recording the coefficients
nstats <- 4
# G matrix stores data for output
G <- matrix("", nrow=nvar+nstats, ncol=ncol+1)
G[1,1] <- toString(res$call)
# Save rownames and colnames
G[(nstats+1):(nvar+nstats),1] <- rownames(co)
G[nstats, 2:(ncoll+1)] <- colnames(co)
# Save Coefficients
G[(nstats+1):(nvar+nstats), 2:(ncol+1)] <- formatter(co)
# Save F-stat
G[1,2] <- paste0("F(",f[2],",",f[3],")")
G[2,2] <- formatter(f[1])
# Save F-p value
G[1,3] <- "Prob > P"
G[2,3] <- formatter(1-pf(f[1],f[2],f[3]))
# Save R2
G[1,4] <- "R-Squared"
G[2,4] <- formatter(res$r.squared)
# Save Adj-R2
G[1,5] <- "Adj-R2"
G[2,5] <- formatter(res$adj.r.squared)
print(G)
if (writecsv) write.csv(G, file=file, row.names=F)
}
lmOut(res)
# First let's generate some fake binary response data (from yesterday's post).
Nobs <- 10^4
X <- cbind(cons=1, X1=rnorm(Nobs),X2=rnorm(Nobs),X3=rnorm(Nobs),u=rnorm(Nobs))
B <- c(B0=-.2, B1=-.1,B2=0,B3=-.2,u=5)
Y <- X%*%B
SData <- as.data.frame(cbind(Y, X))
# Great, we have generated our data.
myres <- lm(Y ~ X1 + X2 + X3, data=SData)
lmOut(myres, file="my-results.csv")
@weiqinwur

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@weiqinwur weiqinwur commented Dec 31, 2013

Dear Francis,

Thank you very much indeed for your code : )
When I run the code, it showed an error as below:
Error in ncol + 1 : non-numeric argument to binary operator
How to fix it?

Kind regards,
Wei

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@ghost ghost commented Mar 5, 2014

Thank you for the code! There is a small typo (ncoll instead of ncol) in line 7 that causes the "Error in ncol+1: non-numeric argument to binary operator". Here is the full code:

lmOut <- function(res, file="test.csv", ndigit=3, writecsv=T) {
# If summary has not been run on the model then run summary
if (length(grep("summary", class(res)))==0) res <- summary(res)
co <- res$coefficients
nvar <- nrow(co)
ncol <- ncol(co)
f <- res$fstatistic
formatter <- function(x) format(round(x,ndigit),nsmall=ndigit)
# This sets the number of rows before we start recording the coefficients
nstats <- 4
# G matrix stores data for output
G <- matrix("", nrow=nvar+nstats, ncol=ncol+1)
G[1,1] <- toString(res$call)
# Save rownames and colnames
G[(nstats+1):(nvar+nstats),1] <- rownames(co)
G[nstats, 2:(ncoll+1)] <- colnames(co)
# Save Coefficients
G[(nstats+1):(nvar+nstats), 2:(ncol+1)] <- formatter(co)
# Save F-stat
G[1,2] <- paste0("F(",f[2],",",f[3],")")
G[2,2] <- formatter(f[1])
# Save F-p value
G[1,3] <- "Prob > P"
G[2,3] <- formatter(1-pf(f[1],f[2],f[3]))
# Save R2
G[1,4] <- "R-Squared"
G[2,4] <- formatter(res$r.squared)
# Save Adj-R2
G[1,5] <- "Adj-R2"
G[2,5] <- formatter(res$adj.r.squared)
print(G)
if (writecsv) write.csv(G, file=file, row.names=F)
}

lmOut(res)

# First let's generate some fake binary response data (from yesterday's post).
Nobs <- 10^4
X <- cbind(cons=1, X1=rnorm(Nobs),X2=rnorm(Nobs),X3=rnorm(Nobs),u=rnorm(Nobs))
B <- c(B0=-.2, B1=-.1,B2=0,B3=-.2,u=5)
Y <- X%*%B
SData <- as.data.frame(cbind(Y, X))

# Great, we have generated our data.
myres <- lm(Y ~ X1 + X2 + X3, data=SData)

lmOut(myres, file="my-results.csv")
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@EconometricsBySimulation EconometricsBySimulation commented Mar 25, 2014

# Excel summary exporter

Modified from Smart, Francis

Jean P. Gibert, 2014

lmOut <- function(res, file="test.csv", ndigit=3, writecsv=T) {

If summary has not been run on the model then run summary

if (length(grep("summary", class(res)))==0) res <- summary(res)
co <- res$coefficients
nvar <- nrow(co)
ncoll <- ncol(co)
f <- res$fstatistic
formatter <- function(x) format(round(x,ndigit),nsmall=ndigit)

This sets the number of rows before we start recording the coefficients

nstats <- 4

G matrix stores data for output

G <- matrix("", nrow=(nvar+nstats), ncol=(ncoll+1))
G[1,1] <- toString(res$call)

Save rownames and colnames

G[(nstats+1):(nvar+nstats),1] <- rownames(co)
G[nstats, 2:(ncoll+1)] <- colnames(co)

Save Coefficients

G[(nstats+1):(nvar+nstats), 2:(ncoll+1)] <- formatter(co)

Save F-stat

G[1,2] <- paste("F(",f[2],",",f[3],")")
G[2,2] <- formatter(f[1])

Save F-p value

G[1,3] <- "Prob > P"
G[2,3] <- formatter(1-pf(f[1],f[2],f[3]))

Save R2

G[1,4] <- "R-Squared"
G[2,4] <- formatter(res$r.squared)

Save Adj-R2

G[1,5] <- "Adj-R2"
G[2,5] <- formatter(res$adj.r.squared)
print(G)
write.csv(G, file=file, row.names=F)
}

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@EconometricsBySimulation EconometricsBySimulation commented Mar 25, 2014

Thanks for the corrections!

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@tonytonycc tonytonycc commented Jun 19, 2014

Hi,

This function is great and I appreciate you putting it together. Question that I can't figure out unfortunately (I am a beginner.)

Trying to loop the output for multiple regressions that I'm doing across monthly samples.

This works fine: lmOut(m_2014-01-31,file="my-results.csv")

But the loop below (where monthschar[1]= 2014-01-31) does not work and returns:
Error in res$coefficients : $ operator is invalid for atomic vectors

for (i in 1:length(monthschar)) {
lmOut(paste("m_",monthschar[i],sep="",paste("",sep="")),
file=paste("output",monthschar[i],sep=""),paste(".csv",sep=""))
}

Any idea why this is happening? The silly quotation marks (`) that R put around the models I generated with another for loop are the reason I attached the ugly paste notation.

Thank you!

@YukunZhang

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@YukunZhang YukunZhang commented Dec 18, 2014

Hi

Thanks for the function. I encounter this error:
Error in matrix("", nrow = (nvar + nstats), ncol = (ncoll + 1)) :
invalid 'nrow' value (too large or NA)

I am using a linear mixed effect model.
Thanks

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@amacharia amacharia commented Feb 19, 2015

thanks for the code ...I am also a beginner and it is very useful... thanks for putting putting some sense into to responder2 on R bloogers... http://www.r-bloggers.com/export-r-results-tables-to-excel-please-dont-kick-me-out-of-your-club/

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@avinavsinha avinavsinha commented Jan 6, 2016

Just curious, why haven't you made this into a package?

@MichaelChirico

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@MichaelChirico MichaelChirico commented Apr 29, 2018

much more canonical than

if (length(grep("summary", class(res)))==0)

would be

if (inherits(res, 'summary.lm'))
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@edb983 edb983 commented Jun 11, 2018

Thank you this is very helpful. I did notice that line 7 and line 17 and 19 all need to be consistent "ncol" or "ncoll" .

@MichaelChirico: I change
"if (length(grep("summary", class(res)))==0) res <- summary(res) "
to
" if (inherits(res, 'summary.lm')) res <- summary(res)"

but then the function throws an error:

"Error in matrix("", nrow = nvar + nstats, ncol = ncol + 1) :
invalid 'nrow' value (too large or NA)"

The original version does produce the "my-results.csv" output file.

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@chrissy-briggs chrissy-briggs commented Oct 9, 2018

Hello, many thanks for this :) I'm trying to run it but I'm getting the following error:

Error in grep("summary", class(res)) : object 'res' not found

Apologies if this is something basic, I am very, very new to R!
Thanks

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@adhartas adhartas commented Jul 30, 2020

Hi, really helpful! is there any version of this function that works with logistic regressions?

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