Re: [ESS] [EXTERNAL] Re: How to Duplicate Previous Functionality/Workflow
On Tue, Sep 26, 2023, at 2:38 PM, Bassett Jr,Roland L via ESS-help wrote:
> Thanks to everyone for their responses - you've definitely helped with
> most of my questions. One still remains, though:
>
> How can I customize the weaver and the exporter so that it doesn't ask
> each time? It seems as though there should be a way to customize each
> of these, but I can't figure out what it is.
I agree, it does seem like this ought to be customizable! I looked into the
code a bit, and from what I can see there's no option to change it, beyond
over-writing the existing functions.
- Tyler
>
> Roland Bassett
> Principal Biostatistician
> Department of Biostatistics - Unit 1411
> Faculty Center Tower FCT4.6071
> The University of Texas M. D. Anderson Cancer Center
> P.O. Box 301402
> Houston, TX 77230
>
> Phone: 713-563-4272
> Fax: 713-563-4242
> Email: rlbas...@mdanderson.org
>
> -Original Message-
> From: ESS-help On Behalf Of Tyler
> Smith via ESS-help
> Sent: Saturday, September 23, 2023 10:38 AM
> To: Stephen J. Eglen
> Cc: ESS-help
> Subject: [EXTERNAL] Re: [ESS] How to Duplicate Previous
> Functionality/Workflow
>
> THIS EMAIL IS A PHISHING RISK
> Do you trust the sender?
> The email address is: ess-help-boun...@r-project.org
> While this email has passed our filters, we need you to review with
> caution before taking any action.
> If the email looks at all suspicious, click the Report a Phish
> button.
>
> On Fri, Sep 22, 2023, at 2:04 AM, Stephen J. Eglen wrote:
>>> (You probably didn't do this, because Docview isn't great for pdfs.
>>> The now abandoned package pdf-tools was a great option for reading
>>> pdfs inside Emacs).
>>
>> just to add a couple of comments:
>>
>> 1. pdf-tools was forked about 1-2 years ago, and now active at:
>>
>> https://urldefense.com/v3/__https://github.com/vedang/pdf-tools__;!!Pf
>> beBCCAmug!hJB8MImjmlLQXcAB-LAswXJZi7hbkrS4q5t30Qi2hgkPBMiYQFEMW4gXbr-6
>> hVAcqLnnAh9bX0OFHLbHRmIz8Hs$
>>
>> It can be a bit fussy to install compared to most Emacs packages,
>> because of dependencies and the binaries it creates. However, I like
>> it and use it regularly.
>>
>
> Thanks, that's great news! pdf-tools was my preferred pdf viewer when
> it was active. I'll definitely check out the new fork
>
> ty
>
> __
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>
> The information contained in this e-mail message may be ...{{dropped:11}}
>
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Re: [ESS] [EXTERNAL] Re: How to Duplicate Previous Functionality/Workflow
Thanks to everyone for their responses - you've definitely helped with most of
my questions. One still remains, though:
How can I customize the weaver and the exporter so that it doesn't ask each
time? It seems as though there should be a way to customize each of these, but
I can't figure out what it is.
Roland Bassett
Principal Biostatistician
Department of Biostatistics - Unit 1411
Faculty Center Tower FCT4.6071
The University of Texas M. D. Anderson Cancer Center
P.O. Box 301402
Houston, TX 77230
Phone: 713-563-4272
Fax: 713-563-4242
Email: rlbas...@mdanderson.org
-Original Message-
From: ESS-help On Behalf Of Tyler Smith via
ESS-help
Sent: Saturday, September 23, 2023 10:38 AM
To: Stephen J. Eglen
Cc: ESS-help
Subject: [EXTERNAL] Re: [ESS] How to Duplicate Previous Functionality/Workflow
THIS EMAIL IS A PHISHING RISK
Do you trust the sender?
The email address is: ess-help-boun...@r-project.org
While this email has passed our filters, we need you to review with caution
before taking any action.
If the email looks at all suspicious, click the Report a Phish button.
On Fri, Sep 22, 2023, at 2:04 AM, Stephen J. Eglen wrote:
>> (You probably didn't do this, because Docview isn't great for pdfs.
>> The now abandoned package pdf-tools was a great option for reading
>> pdfs inside Emacs).
>
> just to add a couple of comments:
>
> 1. pdf-tools was forked about 1-2 years ago, and now active at:
>
> https://urldefense.com/v3/__https://github.com/vedang/pdf-tools__;!!Pf
> beBCCAmug!hJB8MImjmlLQXcAB-LAswXJZi7hbkrS4q5t30Qi2hgkPBMiYQFEMW4gXbr-6
> hVAcqLnnAh9bX0OFHLbHRmIz8Hs$
>
> It can be a bit fussy to install compared to most Emacs packages,
> because of dependencies and the binaries it creates. However, I like
> it and use it regularly.
>
Thanks, that's great news! pdf-tools was my preferred pdf viewer when it was
active. I'll definitely check out the new fork
ty
__
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Re: [ESS] Have M-x R point at the most recent version of R
I put it on the path,
Windows key -> Edit the system environment variables -> Environment
variables... -> Double click Path -> add C:\Program
Files\R\R-devel\bin\x64 or whatever
On Tue, Sep 26, 2023 at 3:07 AM Hüsing, Johannes via ESS-help
wrote:
>
> Dear ESS-helping crowd,
> following the advice on https://r-pkgs.org/setup.html, I installed R version
> 4.3.1 for MS Windows from CRAN.
>
> How do I communicate to ESS that a new version has been installed? I read the
> advice on
> https://emacs.stackexchange.com/questions/60681/ess-start-process-does-not-include-new-r-version,
> I used the Emacs customisation dialogue to set ess-rterm-version-paths from
> C:/Program Files/R/R-4.2.2/bin/x64/Rterm.exe to C:/Program
> Files/R/R-4.3.1/bin/x64/Rterm.exe. After that, the variable
> ess-r-runner-prefixes, as well as ess-r-versions resolves to ("R-1" "R-2"
> "R-3" "R-4" "R-5" "R-6" "R-7" "R-devel" "R-patched"), and both M-x R and M-x
> R-newest will start R 4.2.2. The variable ess-r-versions-created resolves to
> (R-4.2.2-64bit), as does its alias ess-r-created-runners. Neither of these is
> customizable in the Emacs dialog.
>
> Is there a way to proceed to notify ESS about the new version installed?
> RStudio opened a miniscule dialog window indicating that it detected
> conflicting versions and had me choose one of them.
>
> Thanks for any hint.
>
>
>
> Dr. Johannes Hüsing
> Epidemiologie
>
> Landeskrebsregister NRW gGmbH
> Gesundheitscampus 10
> 44801 Bochum
>
>
>
> T 0234 54509-216
> F 0234 54509-499
> johannes.hues...@krebsregister.nrw.de
> www.landeskrebsregister.nrw
>
> Das Landeskrebsregister NRW online
> FACEBOOK:
> www.facebook.com/LKR.NordrheinWestfalen
> INSTAGRAM: https://www.instagram.com/landeskrebsregister_nrw
> NEWSLETTER: https://www.landeskrebsregister.nrw/aktuelles/newsletter
>
>
> Geschäftsführer
> Dr. Andres Schützendübel
> Vorsitzender der Gesellschafterversammlung
> Staatssekretär Matthias Heidmeier
> Sitz der Gesellschaft
> Bochum
> Registergericht
> Amtsgericht Bochum
> HRB 17715
>
> HINWEIS: Diese Nachricht ist nur für den Adressaten bestimmt. Es ist nicht
> erlaubt, diese Nachricht zu kopieren oder Dritten zugänglich zu machen.
> Sollten Sie irrtümlich diese Nachricht erhalten haben, bitte ich um Ihre
> Mitteilung per E-Mail oder unter der oben angegebenen Telefonnummer.
>
> [[alternative HTML version deleted]]
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Re: [R] car::deltaMethod() fails when a particular combination of categorical variables is not present
Dear Michael, My previous response was inaccurate: First, linearHypothesis() *is* able to accommodate aliased coefficients by setting the argument singular.ok = TRUE: > linearHypothesis(minimal_model, "bt2 + csent + bt2:csent = 0", + singular.ok=TRUE) Linear hypothesis test: bt2 + csent + bt2:csent = 0 Model 1: restricted model Model 2: a ~ b * c Res.DfRSS Df Sum of Sq F Pr(>F) 1 16 9392.1 2 15 9266.4 1125.67 0.2034 0.6584 Moreover, when there is an empty cell, this F-test is (for a reason that I haven't worked out, but is almost surely due to how the rank-deficient model is parametrized) *not* equivalent to the t-test for the corresponding coefficient in the raveled version of the two factors: > df$bc <- factor(with(df, paste(b, c, sep=":"))) > m <- lm(a ~ bc, data=df) > summary(m) Call: lm(formula = a ~ bc, data = df) Residuals: Min 1Q Median 3Q Max -57.455 -11.750 0.439 14.011 37.545 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept)20.50 17.57 1.166 0.2617 bct1:unsent37.50 24.85 1.509 0.1521 bct2:other 32.00 24.85 1.287 0.2174 bct2:sent 17.17 22.69 0.757 0.4610 <<< cf. F = 0.2034, p = 0.6584 bct2:unsent38.95 19.11 2.039 0.0595 Residual standard error: 24.85 on 15 degrees of freedom Multiple R-squared: 0.2613,Adjusted R-squared: 0.06437 F-statistic: 1.327 on 4 and 15 DF, p-value: 0.3052 In the full-rank case, however, what I said is correct -- that is, the F-test for the 1 df hypothesis on the three coefficients is equivalent to the t-test for the corresponding coefficient when the two factors are raveled: > linearHypothesis(minimal_model_fixed, "bt2 + csent + bt2:csent = 0") Linear hypothesis test: bt2 + csent + bt2:csent = 0 Model 1: restricted model Model 2: a ~ b * c Res.DfRSS Df Sum of Sq F Pr(>F) 1 15 9714.5 2 14 9194.4 1520.08 0.7919 0.3886 > df_fixed$bc <- factor(with(df_fixed, paste(b, c, sep=":"))) > m <- lm(a ~ bc, data=df_fixed) > summary(m) Call: lm(formula = a ~ bc, data = df_fixed) Residuals: Min 1Q Median 3Q Max -57.455 -11.750 0.167 14.011 37.545 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 64.000 25.627 2.497 0.0256 bct1:sent-43.500 31.387 -1.386 0.1874 bct1:unsent -12.000 36.242 -0.331 0.7455 bct2:other -11.500 31.387 -0.366 0.7195 bct2:sent-26.333 29.591 -0.890 0.3886 << cf. bct2:unsent -4.545 26.767 -0.170 0.8676 Residual standard error: 25.63 on 14 degrees of freedom Multiple R-squared: 0.2671,Adjusted R-squared: 0.005328 F-statistic: 1.02 on 5 and 14 DF, p-value: 0.4425 So, to summarize: (1) You can use linearHypothesis() with singular.ok=TRUE to test the hypothesis that you specified, though I suspect that this hypothesis probably isn't testing what you think in the rank-deficient case. I suspect that the hypothesis that you want to test is obtained by raveling the two factors. (2) There is no reason to use deltaMethod() for a linear hypothesis, but there is also no intrinsic reason that deltaMethod() shouldn't be able to handle a rank-deficient model. We'll probably fix that. My apologies for the confusion, John -- John Fox, Professor Emeritus McMaster University Hamilton, Ontario, Canada web: https://www.john-fox.ca/ On 2023-09-26 9:49 a.m., John Fox wrote: Caution: External email. Dear Michael, You're testing a linear hypothesis, so there's no need to use the delta method, but the linearHypothesis() function in the car package also fails in your case: > linearHypothesis(minimal_model, "bt2 + csent + bt2:csent = 0") Error in linearHypothesis.lm(minimal_model, "bt2 + csent + bt2:csent = 0") : there are aliased coefficients in the model. One work-around is to ravel the two factors into a single factor with 5 levels: > df$bc <- factor(with(df, paste(b, c, sep=":"))) > df$bc [1] t2:unsent t2:unsent t2:unsent t2:unsent t2:sent t2:unsent [7] t2:unsent t1:sent t2:unsent t2:unsent t2:other t2:unsent [13] t1:unsent t1:sent t2:unsent t2:other t1:unsent t2:sent [19] t2:sent t2:unsent Levels: t1:sent t1:unsent t2:other t2:sent t2:unsent > m <- lm(a ~ bc, data=df) > summary(m) Call: lm(formula = a ~ bc, data = df) Residuals: Min 1Q Median 3Q Max -57.455 -11.750 0.439 14.011 37.545 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 20.50 17.57 1.166 0.2617 bct1:unsent 37.50 24.85 1.509 0.1521 bct2:other 32.00 24.85 1.287 0.2174 bct2:sent 17.17 22.69 0.757 0.4610 bct2:unsent 38.95 19.11 2.039 0.0595 Residual standard error: 24.85 on 15 degrees of freedom Multiple R-squared: 0.2613, Adjusted R-squared: 0.06437 F-statistic: 1.327 on 4 and 15 DF, p-value: 0.3052 Then the hypothesis is tested
Re: [R] data.table installation on intel macOS Ventura 13.6
Hi,
This is the Makevars I used to compile sucessfully the latest version of
data.table in a x86_64 machine.
#--
#--- https://github.com/Rdatatable/data.table/wiki/Installation
#-
LOC = /usr/local/gfortran
CC=$(LOC)/bin/gcc -fopenmp
CXX=$(LOC)/bin/g++ -fopenmp
CXX11 = $(LOC)/bin/g++ -fopenmp # for fst package
CFLAGS=-g -O3 -Wall -pedantic -std=gnu99 -mtune=native -pipe
CXXFLAGS=-g -O3 -Wall -pedantic -std=c++11 -mtune=native -pipe
LDFLAGS=-L$(LOC)/lib -Wl,-rpath,$(LOC)/lib
CPPFLAGS=-I$(LOC)/include
-I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include
#--
I had to install "gfortran" which has a link in that installation page.
Having "gfortran" was key to make it run multithread.
Thanks,
Carlos.
On Tue, Sep 26, 2023 at 11:49 AM Naresh Gurbuxani <
naresh_gurbux...@hotmail.com> wrote:
> > Sys.info()
>
>sysname
>
> "Darwin"
>
>release
>
> "22.6.0"
>
>version
> "Darwin Kernel Version 22.6.0: Fri Sep 15 13:39:52 PDT 2023;
> root:xnu-8796.141.3.700.8~1/RELEASE_X86_64"
>
> nodename
>
> [deleted]
>
>machine
>
> "x86_64"
>
> login
>
> [deleted]
>
> user
>
> [deleted]
>
> effective_user
>
> [deleted]
>
> My Makevars file:
> CPPFLAGS += -Xclang -fopenmp
> LDFLAGS += -lomp
>
> Using brew, I installed libomp
>
> data.table is not installed on my machine. In fresh R session:
> > install.packages("data.table", repos = "https://cran.r-project.org;)
> Installing package into ‘/usr/local/lib/R/4.3/site-library’
> (as ‘lib’ is unspecified)
> trying URL '
> https://cran.r-project.org/src/contrib/data.table_1.14.8.tar.gz'
> Content type 'application/x-gzip' length 5338582 bytes (5.1 MB)
> ==
> downloaded 5.1 MB
>
> * installing *source* package ‘data.table’ ...
> ** package ‘data.table’ successfully unpacked and MD5 sums checked
> ** using staged installation
> zlib 1.2.11 is available ok
> *** OpenMP not supported! data.table uses OpenMP to automatically
> *** parallelize operations like sorting, grouping, file reading, etc.
> *** For details on how to install the necessary toolchains on your OS see:
> *** https://github.com/Rdatatable/data.table/wiki/Installation
> *** Continuing installation without OpenMP support...
> ** libs
> using C compiler: ‘Homebrew clang version 17.0.1’
> using SDK: ‘’
> clang -I"/usr/local/Cellar/r/4.3.1/lib/R/include" -DNDEBUG
> -I/usr/local/opt/gettext/include -I/usr/local/opt/readline/include
> -I/usr/local/opt/xz/include -I/usr/local/include -Xclang -fopenmp-fPIC
> -g -O2 -c assign.c -o assign.o
> [several lines deleted]
> clang -dynamiclib -Wl,-headerpad_max_install_names -undefined
> dynamic_lookup -single_module -multiply_defined suppress
> -L/usr/local/Cellar/r/4.3.1/lib/R/lib -L/usr/local/opt/gettext/lib
> -L/usr/local/opt/readline/lib -L/usr/local/opt/xz/lib -L/usr/local/lib
> -lomp -o data.table.so assign.o between.o bmerge.o chmatch.o cj.o
> coalesce.o dogroups.o fastmean.o fcast.o fifelse.o fmelt.o forder.o frank.o
> fread.o freadR.o froll.o frollR.o frolladaptive.o fsort.o fwrite.o
> fwriteR.o gsumm.o ijoin.o init.o inrange.o nafill.o nqrecreateindices.o
> openmp-utils.o quickselect.o rbindlist.o reorder.o shift.o snprintf.o
> subset.o transpose.o types.o uniqlist.o utils.o vecseq.o wrappers.o -lz
> -L/usr/local/Cellar/r/4.3.1/lib/R/lib -lR -lintl -Wl,-framework
> -Wl,CoreFoundation
> ld: warning: -single_module is obsolete
> ld: warning: -multiply_defined is obsolete
> ld: warning: -single_module is obsolete
> ld: warning: -multiply_defined is obsolete
> ld: library 'omp' not found
> clang: error: linker command failed with exit code 1 (use -v to see
> invocation)
> make: *** [data.table.so] Error 1
> ERROR: compilation failed for package ‘data.table’
> * removing ‘/usr/local/lib/R/4.3/site-library/data.table’
>
> The downloaded source packages are in
>
> ‘/private/var/folders/97/5377j5_d207fshvjz_pz7szwgn/T/RtmpjZgIo0/downloaded_packages’
> Warning message:
> In install.packages("data.table", repos = "https://cran.r-project.org;) :
> installation of package ‘data.table’ had non-zero exit status
>
> I delete above two lines from my Makevars fiie, which is now empty. Now
> reinstall data.table.
>
> > install.packages("data.table", repos = "https://cran.r-project.org;)
> Installing package into ‘/usr/local/lib/R/4.3/site-library’
> (as ‘lib’ is unspecified)
> trying URL '
> https://cran.r-project.org/src/contrib/data.table_1.14.8.tar.gz'
> Content type 'application/x-gzip' length 5338582 bytes (5.1 MB)
> ==
> downloaded 5.1 MB
>
> * installing *source* package ‘data.table’ ...
> ** package ‘data.table’ successfully unpacked and MD5 sums checked
>
Re: [R] car::deltaMethod() fails when a particular combination of categorical variables is not present
Dear Michael,
You're testing a linear hypothesis, so there's no need to use the delta
method, but the linearHypothesis() function in the car package also
fails in your case:
> linearHypothesis(minimal_model, "bt2 + csent + bt2:csent = 0")
Error in linearHypothesis.lm(minimal_model, "bt2 + csent + bt2:csent = 0") :
there are aliased coefficients in the model.
One work-around is to ravel the two factors into a single factor with 5
levels:
> df$bc <- factor(with(df, paste(b, c, sep=":")))
> df$bc
[1] t2:unsent t2:unsent t2:unsent t2:unsent t2:sent t2:unsent
[7] t2:unsent t1:sent t2:unsent t2:unsent t2:other t2:unsent
[13] t1:unsent t1:sent t2:unsent t2:other t1:unsent t2:sent
[19] t2:sent t2:unsent
Levels: t1:sent t1:unsent t2:other t2:sent t2:unsent
> m <- lm(a ~ bc, data=df)
> summary(m)
Call:
lm(formula = a ~ bc, data = df)
Residuals:
Min 1Q Median 3Q Max
-57.455 -11.750 0.439 14.011 37.545
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept)20.50 17.57 1.166 0.2617
bct1:unsent37.50 24.85 1.509 0.1521
bct2:other 32.00 24.85 1.287 0.2174
bct2:sent 17.17 22.69 0.757 0.4610
bct2:unsent38.95 19.11 2.039 0.0595
Residual standard error: 24.85 on 15 degrees of freedom
Multiple R-squared: 0.2613,Adjusted R-squared: 0.06437
F-statistic: 1.327 on 4 and 15 DF, p-value: 0.3052
Then the hypothesis is tested directly by the t-value for the
coefficient bct2:sent.
I hope that this helps,
John
--
John Fox, Professor Emeritus
McMaster University
Hamilton, Ontario, Canada
web: https://www.john-fox.ca/
On 2023-09-26 1:12 a.m., Michael Cohn wrote:
Caution: External email.
I'm running a linear regression with two categorical predictors and their
interaction. One combination of levels does not occur in the data, and as
expected, no parameter is estimated for it. I now want to significance test
a particular combination of levels that does occur in the data (ie, I want
to get a confidence interval for the total prediction at given levels of
each variable).
In the past I've done this using car::deltaMethod() but in this dataset
that does not work, as shown in the example below: The regression model
gives the expected output, but deltaMethod() gives this error:
error in t(gd) %*% vcov. : non-conformable arguments
I believe this is because there is no parameter estimate for when the
predictors have the values 't1' and 'other'. In the df_fixed dataframe,
putting one person into that combination of categories causes deltaMethod()
to work as expected.
I don't know of any theoretical reason that missing one interaction
parameter estimate should prevent getting a confidence interval for a
different combination of predictors. Is there a way to use deltaMethod() or
some other function to do this without changing my data?
Thank you,
- Michael Cohn
Vote Rev (http://voterev.org)
Demonstration:
--
library(car)
# create dataset with outcome and two categorical predictors
outcomes <- c(91,2,60,53,38,78,48,33,97,41,64,84,64,8,66,41,52,18,57,34)
persontype <-
c("t2","t2","t2","t2","t2","t2","t2","t1","t2","t2","t2","t2","t1","t1","t2","t2","t1","t2","t2","t2")
arm_letter <-
c("unsent","unsent","unsent","unsent","sent","unsent","unsent","sent","unsent","unsent","other","unsent","unsent","sent","unsent","other","unsent","sent","sent","unsent")
df <- data.frame(a = outcomes, b=persontype, c=arm_letter)
# note: there are no records with the combination 't1' + 'other'
table(df$b,df$c)
#regression works as expected
minimal_formula <- formula("a ~ b*c")
minimal_model <- lm(minimal_formula, data=df)
summary(minimal_model)
#use deltaMethod() to get a prediction for individuals with the combination
'b2' and 'sent'
# deltaMethod() fails with "error in t(gd) %*% vcov. : non-conformable
arguments."
deltaMethod(minimal_model, "bt2 + csent + `bt2:csent`", rhs=0)
# duplicate the dataset and change one record to be in the previously empty
cell
df_fixed <- df
df_fixed[c(13),"c"] <- 'other'
table(df_fixed$b,df_fixed$c)
#deltaMethod() now works
minimal_model_fixed <- lm(minimal_formula, data=df_fixed)
deltaMethod(minimal_model_fixed, "bt2 + csent + `bt2:csent`", rhs=0)
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Re: [R] RQuantLib installation problem
Updating to latest version of R and reinstalling RQuantLib worked.
Thanks
> On Sep 24, 2023, at 5:29 PM, David Winsemius wrote:
>
>
> On 9/24/23 08:23, Ivan Krylov wrote:
>> On Sun, 24 Sep 2023 02:19:20 +
>> Naresh Gurbuxani wrote:
>>
install.packages("RQuantLib", repos = "https://cran.r-project.org;)
>>> Installing package into ‘/usr/local/lib/R/4.1/site-library’
>>> (as ‘lib’ is unspecified)
>>> trying URL
>>> 'https://cran.r-project.org/src/contrib/RQuantLib_0.4.17.tar.gz'
>
>
> Ivan is undoubtedly more knowledgeable on these matters than I, but I noticed
> that you are trying to install the current version of RQuantLib into a
> library that appears associated with a significantly older version of R than
> is current the current version. (And I second the advice that this is a
> question properly addressed to the R_SIG-mac mailing list but only with a
> much better description of version of your setup and how R was installed. You
> might want to install RQuantLib for a time frame that matched R 4.1.x. The
> archive is here:
>
> https://cran.r-project.org/src/contrib/00Archive/RQuantLib/
>
> You may also want to set the compile flags so that R can find your version of
> gfortran. That can be done within install.packages but most experts would
> prefer that you do it from a system terminal session with $ R CMD INSTALL.
> You can find details at the r help page `
>
> ?INSTALL -- David
>
>>
>>> dyld[29996]: Library not loaded:
>>> /usr/local/opt/gcc/lib/gcc/11/libgfortran.5.dylib
>>> Referenced from: <383F3774-06DE-3792-AA2C-C9D6B37A2D89>
>>> /usr/local/Cellar/r/4.1.2/lib/R/lib/libR.dylib
>> So you're installing source packages into a Homebrew-built R, and they
>> fail to load after being compiled?
>>
>> If you don't get an answer here, try r-sig-...@r-project.org or
>> .
>>
__
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] save() and load(): *prefer* saveRDS() and readRDS()
Hi Martin: good morning
Thank you very much for your detailed explanation. Got it now.
With many thanks
Abou
On Tue, Sep 26, 2023, 3:24 AM Martin Maechler
wrote:
> > Jeff Newmiller via R-help
> > on Mon, 25 Sep 2023 18:46:02 -0700 writes:
>
> > You never created any object in R called irisdataTest. Objects in
> the global environment have names that are unrelated to the names of files
> on disk.
> > The load function modifies an environment to create a variable named
> as it was named in the environment from which it was saved. Thus, you
> cannot simply load an object that was saved with one name into an object
> named something else. It is possible to create a new environment to put the
> loaded objects into, but I wouldn't recommend trying to explain how to do
> that to a beginner. Rather, I would instead recommend using saveRDS and
> readRDS instead to save/load exactly one object at a time without storing
> the object name.
>
> > saveRDS( mtcars, "my_mtcars.rds" )
> > new_obj <- readRDS( "my_mtcars.rds" )
>
> > I would also guide them to never save their environment when
> prompted by R... the .RData file this creates will remember mistakes made
> in previous sessions making troubleshooting very difficult later. Instead
> they should focus on making a top-to-bottom script that has all their
> analysis steps so they can start from scratch.
>
> Yes!
>
> And just re-iterating what Jeff mentioned above:
> Notably when teaching, the use of saveRDS() and readRDS()
> should be emphasized as safer / self-documenting, ...
> for the case where there's just one object to save/load.
>
> *and* you can always put several objects into a list and
> saveRDS() / readRDS() that.
>
> Note: Our pkg {sfsmisc} nowadays contains a nice utility function
> list_() ==> help page online e.g. here
>
> https://search.r-project.org/CRAN/refmans/sfsmisc/html/list_named.html
>
> which comes were handy when you want to easily create a *named*
> list from a bunch of objects, as e.g. above to be able to nicely use
>
> saveRDS(list_(obj1, obj2, table3, grob4, data5),
> file = "allthings.rds")
>
> The cute utility is very simply defined as
>
> ##' list_(a, b, cc) creates a *named* list using the actual arguments'
> names
> list_ <- function(...) `names<-`(list(...), vapply(sys.call()[-1L],
> as.character, ""))
>
>
> > On September 25, 2023 6:23:01 PM PDT, AbouEl-Makarim Aboueissa <
> abouelmakarim1...@gmail.com> wrote:
> >> Dear ALL:
> >>
> >> I am teaching statistical packages class this semester, in R
> programing I
> >> am trying to explain the use of save() and load() with an example
> using the
> >> iris data. It seems that the save() function works, BUT when I
> tried to
> >> load the data back to R, it seems that there is a problem(s), I
> could not
> >> figure out what went wrong.
> >>
> >> Any help would be highly appreciated.
> >>
> >>
> >> I saved the iris data in my computer in the text format,
> "iris.with.head.txt
> >> ".
> >>
> >> Here are my R codes:
> >>
> >>> irisdata<-read.table("G:/iris.with.head.txt", header=T)
> >>>
> >>> head(irisdata)
> >> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
> >> 1 5.1 3.5 1.4 0.2 setosa
> >> 2 4.9 3.0 1.4 0.2 setosa
> >> 3 4.7 3.2 1.3 0.2 setosa
> >> 4 4.6 3.1 1.5 0.2 setosa
> >> 5 5.0 3.6 1.4 0.2 setosa
> >> 6 5.4 3.9 1.7 0.4 setosa
> >>
> >>
> >>
> >> *# saving the data as an .rda*
> >>
> >> save(irisdata,file="G:/irisdataTest.rda")
> >>
> >> *# load the data back to R*
> >>
> >> load(file="G:/irisdataTest.rda")
> >>
> >>
> >>> head(irisdataTest)
> >> Error in head(irisdataTest) : object 'irisdataTest' not found
> >>
> >>> irisdataTest
> >> Error: object 'irisdataTest' not found
> >>
> >>
> >>
> >> with many thanks
> >> abou
> >> __
> >>
> >>
> >> *AbouEl-Makarim Aboueissa, PhD*
> >>
> >> *Professor, Mathematics and Statistics*
> >> *Graduate Coordinator*
> >>
> >> *Department of Mathematics and Statistics*
> >> *University of Southern Maine*
> >>
> >> [[alternative HTML version deleted]]
> >>
> >> __
> >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >> 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.
>
> > --
> > Sent from my phone. Please excuse my brevity.
>
> >
Re: [R] save() and load()
Hi Shu: good morning
Thank you very much for your detailed explanation. Got it now.
With many thanks
Abou
On Mon, Sep 25, 2023, 9:39 PM Shu Fai Cheung
wrote:
> Hi,
>
> You can try this:
>
> head(irisdata)
>
> Objects loaded by load() keep their names when being saved. In your
> case, it is 'irisdata'.
>
> You can also use verbose = TRUE to show the names of objects loaded:
>
> load(file = "irisdataTest.RData", verbose = TRUE)
>
> Hope this helps.
>
> Regards,
> Shu Fai
>
> On Tue, Sep 26, 2023 at 9:24 AM AbouEl-Makarim Aboueissa
> wrote:
> >
> > Dear ALL:
> >
> > I am teaching statistical packages class this semester, in R programing I
> > am trying to explain the use of save() and load() with an example using
> the
> > iris data. It seems that the save() function works, BUT when I tried to
> > load the data back to R, it seems that there is a problem(s), I could not
> > figure out what went wrong.
> >
> > Any help would be highly appreciated.
> >
> >
> > I saved the iris data in my computer in the text format,
> "iris.with.head.txt
> > ".
> >
> > Here are my R codes:
> >
> > > irisdata<-read.table("G:/iris.with.head.txt", header=T)
> > >
> > > head(irisdata)
> > Sepal.Length Sepal.Width Petal.Length Petal.Width Species
> > 1 5.1 3.5 1.4 0.2 setosa
> > 2 4.9 3.0 1.4 0.2 setosa
> > 3 4.7 3.2 1.3 0.2 setosa
> > 4 4.6 3.1 1.5 0.2 setosa
> > 5 5.0 3.6 1.4 0.2 setosa
> > 6 5.4 3.9 1.7 0.4 setosa
> >
> >
> >
> > *# saving the data as an .rda*
> >
> > save(irisdata,file="G:/irisdataTest.rda")
> >
> > *# load the data back to R*
> >
> > load(file="G:/irisdataTest.rda")
> >
> >
> > >head(irisdataTest)
> > Error in head(irisdataTest) : object 'irisdataTest' not found
> >
> > > irisdataTest
> > Error: object 'irisdataTest' not found
> >
> >
> >
> > with many thanks
> > abou
> > __
> >
> >
> > *AbouEl-Makarim Aboueissa, PhD*
> >
> > *Professor, Mathematics and Statistics*
> > *Graduate Coordinator*
> >
> > *Department of Mathematics and Statistics*
> > *University of Southern Maine*
> >
> > [[alternative HTML version deleted]]
> >
> > __
> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > 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.
>
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.
Re: [R] save() and load()
Hi Jeff: good morning
Thank you very much for your detailed explanation. Got it now.
With many thanks
Abou
On Mon, Sep 25, 2023, 9:46 PM Jeff Newmiller
wrote:
> You never created any object in R called irisdataTest. Objects in the
> global environment have names that are unrelated to the names of files on
> disk.
>
> The load function modifies an environment to create a variable named as it
> was named in the environment from which it was saved. Thus, you cannot
> simply load an object that was saved with one name into an object named
> something else. It is possible to create a new environment to put the
> loaded objects into, but I wouldn't recommend trying to explain how to do
> that to a beginner. Rather, I would instead recommend using saveRDS and
> readRDS instead to save/load exactly one object at a time without storing
> the object name.
>
> saveRDS( mtcars, "my_mtcars.rds" )
> new_obj <- readRDS( "my_mtcars.rds" )
>
> I would also guide them to never save their environment when prompted by
> R... the .RData file this creates will remember mistakes made in previous
> sessions making troubleshooting very difficult later. Instead they should
> focus on making a top-to-bottom script that has all their analysis steps so
> they can start from scratch.
>
> On September 25, 2023 6:23:01 PM PDT, AbouEl-Makarim Aboueissa <
> abouelmakarim1...@gmail.com> wrote:
> >Dear ALL:
> >
> >I am teaching statistical packages class this semester, in R programing I
> >am trying to explain the use of save() and load() with an example using
> the
> >iris data. It seems that the save() function works, BUT when I tried to
> >load the data back to R, it seems that there is a problem(s), I could not
> >figure out what went wrong.
> >
> >Any help would be highly appreciated.
> >
> >
> >I saved the iris data in my computer in the text format,
> "iris.with.head.txt
> >".
> >
> >Here are my R codes:
> >
> >> irisdata<-read.table("G:/iris.with.head.txt", header=T)
> >>
> >> head(irisdata)
> > Sepal.Length Sepal.Width Petal.Length Petal.Width Species
> >1 5.1 3.5 1.4 0.2 setosa
> >2 4.9 3.0 1.4 0.2 setosa
> >3 4.7 3.2 1.3 0.2 setosa
> >4 4.6 3.1 1.5 0.2 setosa
> >5 5.0 3.6 1.4 0.2 setosa
> >6 5.4 3.9 1.7 0.4 setosa
> >
> >
> >
> >*# saving the data as an .rda*
> >
> >save(irisdata,file="G:/irisdataTest.rda")
> >
> >*# load the data back to R*
> >
> >load(file="G:/irisdataTest.rda")
> >
> >
> >>head(irisdataTest)
> >Error in head(irisdataTest) : object 'irisdataTest' not found
> >
> >> irisdataTest
> >Error: object 'irisdataTest' not found
> >
> >
> >
> >with many thanks
> >abou
> >__
> >
> >
> >*AbouEl-Makarim Aboueissa, PhD*
> >
> >*Professor, Mathematics and Statistics*
> >*Graduate Coordinator*
> >
> >*Department of Mathematics and Statistics*
> >*University of Southern Maine*
> >
> > [[alternative HTML version deleted]]
> >
> >__
> >R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >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.
>
> --
> Sent from my phone. Please excuse my brevity.
>
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.
[ESS] Have M-x R point at the most recent version of R
Dear ESS-helping crowd,
following the advice on https://r-pkgs.org/setup.html, I installed R version
4.3.1 for MS Windows from CRAN.
How do I communicate to ESS that a new version has been installed? I read the
advice on
https://emacs.stackexchange.com/questions/60681/ess-start-process-does-not-include-new-r-version,
I used the Emacs customisation dialogue to set ess-rterm-version-paths from
C:/Program Files/R/R-4.2.2/bin/x64/Rterm.exe to C:/Program
Files/R/R-4.3.1/bin/x64/Rterm.exe. After that, the variable
ess-r-runner-prefixes, as well as ess-r-versions resolves to ("R-1" "R-2" "R-3"
"R-4" "R-5" "R-6" "R-7" "R-devel" "R-patched"), and both M-x R and M-x R-newest
will start R 4.2.2. The variable ess-r-versions-created resolves to
(R-4.2.2-64bit), as does its alias ess-r-created-runners. Neither of these is
customizable in the Emacs dialog.
Is there a way to proceed to notify ESS about the new version installed?
RStudio opened a miniscule dialog window indicating that it detected
conflicting versions and had me choose one of them.
Thanks for any hint.
Dr. Johannes H�sing
Epidemiologie
Landeskrebsregister NRW gGmbH
Gesundheitscampus 10
44801 Bochum
T 0234 54509-216
F 0234 54509-499
johannes.hues...@krebsregister.nrw.de
www.landeskrebsregister.nrw
Das Landeskrebsregister NRW online
FACEBOOK:
www.facebook.com/LKR.NordrheinWestfalen
INSTAGRAM: https://www.instagram.com/landeskrebsregister_nrw
NEWSLETTER: https://www.landeskrebsregister.nrw/aktuelles/newsletter
Gesch�ftsf�hrer
Dr. Andres Sch�tzend�bel
Vorsitzender der Gesellschafterversammlung
Staatssekret�r Matthias Heidmeier
Sitz der Gesellschaft
Bochum
Registergericht
Amtsgericht Bochum
HRB 17715
HINWEIS: Diese Nachricht ist nur f�r den Adressaten bestimmt. Es ist nicht
erlaubt, diese Nachricht zu kopieren oder Dritten zug�nglich zu machen. Sollten
Sie irrt�mlich diese Nachricht erhalten haben, bitte ich um Ihre Mitteilung per
E-Mail oder unter der oben angegebenen Telefonnummer.
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__
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https://stat.ethz.ch/mailman/listinfo/ess-help
Re: [R] data.table installation on intel macOS Ventura 13.6
> Sys.info()
sysname
"Darwin"
release
"22.6.0"
version
"Darwin Kernel Version 22.6.0: Fri Sep 15 13:39:52 PDT 2023;
root:xnu-8796.141.3.700.8~1/RELEASE_X86_64"
nodename
[deleted]
machine
"x86_64"
login
[deleted]
user
[deleted]
effective_user
[deleted]
My Makevars file:
CPPFLAGS += -Xclang -fopenmp
LDFLAGS += -lomp
Using brew, I installed libomp
data.table is not installed on my machine. In fresh R session:
> install.packages("data.table", repos = "https://cran.r-project.org;)
Installing package into ‘/usr/local/lib/R/4.3/site-library’
(as ‘lib’ is unspecified)
trying URL 'https://cran.r-project.org/src/contrib/data.table_1.14.8.tar.gz'
Content type 'application/x-gzip' length 5338582 bytes (5.1 MB)
==
downloaded 5.1 MB
* installing *source* package ‘data.table’ ...
** package ‘data.table’ successfully unpacked and MD5 sums checked
** using staged installation
zlib 1.2.11 is available ok
*** OpenMP not supported! data.table uses OpenMP to automatically
*** parallelize operations like sorting, grouping, file reading, etc.
*** For details on how to install the necessary toolchains on your OS see:
*** https://github.com/Rdatatable/data.table/wiki/Installation
*** Continuing installation without OpenMP support...
** libs
using C compiler: ‘Homebrew clang version 17.0.1’
using SDK: ‘’
clang -I"/usr/local/Cellar/r/4.3.1/lib/R/include" -DNDEBUG
-I/usr/local/opt/gettext/include -I/usr/local/opt/readline/include
-I/usr/local/opt/xz/include -I/usr/local/include -Xclang -fopenmp-fPIC -g
-O2 -c assign.c -o assign.o
[several lines deleted]
clang -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup
-single_module -multiply_defined suppress -L/usr/local/Cellar/r/4.3.1/lib/R/lib
-L/usr/local/opt/gettext/lib -L/usr/local/opt/readline/lib
-L/usr/local/opt/xz/lib -L/usr/local/lib -lomp -o data.table.so assign.o
between.o bmerge.o chmatch.o cj.o coalesce.o dogroups.o fastmean.o fcast.o
fifelse.o fmelt.o forder.o frank.o fread.o freadR.o froll.o frollR.o
frolladaptive.o fsort.o fwrite.o fwriteR.o gsumm.o ijoin.o init.o inrange.o
nafill.o nqrecreateindices.o openmp-utils.o quickselect.o rbindlist.o reorder.o
shift.o snprintf.o subset.o transpose.o types.o uniqlist.o utils.o vecseq.o
wrappers.o -lz -L/usr/local/Cellar/r/4.3.1/lib/R/lib -lR -lintl -Wl,-framework
-Wl,CoreFoundation
ld: warning: -single_module is obsolete
ld: warning: -multiply_defined is obsolete
ld: warning: -single_module is obsolete
ld: warning: -multiply_defined is obsolete
ld: library 'omp' not found
clang: error: linker command failed with exit code 1 (use -v to see invocation)
make: *** [data.table.so] Error 1
ERROR: compilation failed for package ‘data.table’
* removing ‘/usr/local/lib/R/4.3/site-library/data.table’
The downloaded source packages are in
‘/private/var/folders/97/5377j5_d207fshvjz_pz7szwgn/T/RtmpjZgIo0/downloaded_packages’
Warning message:
In install.packages("data.table", repos = "https://cran.r-project.org;) :
installation of package ‘data.table’ had non-zero exit status
I delete above two lines from my Makevars fiie, which is now empty. Now
reinstall data.table.
> install.packages("data.table", repos = "https://cran.r-project.org;)
Installing package into ‘/usr/local/lib/R/4.3/site-library’
(as ‘lib’ is unspecified)
trying URL 'https://cran.r-project.org/src/contrib/data.table_1.14.8.tar.gz'
Content type 'application/x-gzip' length 5338582 bytes (5.1 MB)
==
downloaded 5.1 MB
*
Re: [R] save() and load(): *prefer* saveRDS() and readRDS()
> Jeff Newmiller via R-help
> on Mon, 25 Sep 2023 18:46:02 -0700 writes:
> You never created any object in R called irisdataTest. Objects in the
global environment have names that are unrelated to the names of files on disk.
> The load function modifies an environment to create a variable named as
it was named in the environment from which it was saved. Thus, you cannot
simply load an object that was saved with one name into an object named
something else. It is possible to create a new environment to put the loaded
objects into, but I wouldn't recommend trying to explain how to do that to a
beginner. Rather, I would instead recommend using saveRDS and readRDS instead
to save/load exactly one object at a time without storing the object name.
> saveRDS( mtcars, "my_mtcars.rds" )
> new_obj <- readRDS( "my_mtcars.rds" )
> I would also guide them to never save their environment when prompted by
R... the .RData file this creates will remember mistakes made in previous
sessions making troubleshooting very difficult later. Instead they should focus
on making a top-to-bottom script that has all their analysis steps so they can
start from scratch.
Yes!
And just re-iterating what Jeff mentioned above:
Notably when teaching, the use of saveRDS() and readRDS()
should be emphasized as safer / self-documenting, ...
for the case where there's just one object to save/load.
*and* you can always put several objects into a list and
saveRDS() / readRDS() that.
Note: Our pkg {sfsmisc} nowadays contains a nice utility function
list_() ==> help page online e.g. here
https://search.r-project.org/CRAN/refmans/sfsmisc/html/list_named.html
which comes were handy when you want to easily create a *named*
list from a bunch of objects, as e.g. above to be able to nicely use
saveRDS(list_(obj1, obj2, table3, grob4, data5),
file = "allthings.rds")
The cute utility is very simply defined as
##' list_(a, b, cc) creates a *named* list using the actual arguments' names
list_ <- function(...) `names<-`(list(...), vapply(sys.call()[-1L],
as.character, ""))
> On September 25, 2023 6:23:01 PM PDT, AbouEl-Makarim Aboueissa
wrote:
>> Dear ALL:
>>
>> I am teaching statistical packages class this semester, in R programing I
>> am trying to explain the use of save() and load() with an example using
the
>> iris data. It seems that the save() function works, BUT when I tried to
>> load the data back to R, it seems that there is a problem(s), I could not
>> figure out what went wrong.
>>
>> Any help would be highly appreciated.
>>
>>
>> I saved the iris data in my computer in the text format,
"iris.with.head.txt
>> ".
>>
>> Here are my R codes:
>>
>>> irisdata<-read.table("G:/iris.with.head.txt", header=T)
>>>
>>> head(irisdata)
>> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
>> 1 5.1 3.5 1.4 0.2 setosa
>> 2 4.9 3.0 1.4 0.2 setosa
>> 3 4.7 3.2 1.3 0.2 setosa
>> 4 4.6 3.1 1.5 0.2 setosa
>> 5 5.0 3.6 1.4 0.2 setosa
>> 6 5.4 3.9 1.7 0.4 setosa
>>
>>
>>
>> *# saving the data as an .rda*
>>
>> save(irisdata,file="G:/irisdataTest.rda")
>>
>> *# load the data back to R*
>>
>> load(file="G:/irisdataTest.rda")
>>
>>
>>> head(irisdataTest)
>> Error in head(irisdataTest) : object 'irisdataTest' not found
>>
>>> irisdataTest
>> Error: object 'irisdataTest' not found
>>
>>
>>
>> with many thanks
>> abou
>> __
>>
>>
>> *AbouEl-Makarim Aboueissa, PhD*
>>
>> *Professor, Mathematics and Statistics*
>> *Graduate Coordinator*
>>
>> *Department of Mathematics and Statistics*
>> *University of Southern Maine*
>>
>> [[alternative HTML version deleted]]
>>
>> __
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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[R] car::deltaMethod() fails when a particular combination of categorical variables is not present
I'm running a linear regression with two categorical predictors and their
interaction. One combination of levels does not occur in the data, and as
expected, no parameter is estimated for it. I now want to significance test
a particular combination of levels that does occur in the data (ie, I want
to get a confidence interval for the total prediction at given levels of
each variable).
In the past I've done this using car::deltaMethod() but in this dataset
that does not work, as shown in the example below: The regression model
gives the expected output, but deltaMethod() gives this error:
error in t(gd) %*% vcov. : non-conformable arguments
I believe this is because there is no parameter estimate for when the
predictors have the values 't1' and 'other'. In the df_fixed dataframe,
putting one person into that combination of categories causes deltaMethod()
to work as expected.
I don't know of any theoretical reason that missing one interaction
parameter estimate should prevent getting a confidence interval for a
different combination of predictors. Is there a way to use deltaMethod() or
some other function to do this without changing my data?
Thank you,
- Michael Cohn
Vote Rev (http://voterev.org)
Demonstration:
--
library(car)
# create dataset with outcome and two categorical predictors
outcomes <- c(91,2,60,53,38,78,48,33,97,41,64,84,64,8,66,41,52,18,57,34)
persontype <-
c("t2","t2","t2","t2","t2","t2","t2","t1","t2","t2","t2","t2","t1","t1","t2","t2","t1","t2","t2","t2")
arm_letter <-
c("unsent","unsent","unsent","unsent","sent","unsent","unsent","sent","unsent","unsent","other","unsent","unsent","sent","unsent","other","unsent","sent","sent","unsent")
df <- data.frame(a = outcomes, b=persontype, c=arm_letter)
# note: there are no records with the combination 't1' + 'other'
table(df$b,df$c)
#regression works as expected
minimal_formula <- formula("a ~ b*c")
minimal_model <- lm(minimal_formula, data=df)
summary(minimal_model)
#use deltaMethod() to get a prediction for individuals with the combination
'b2' and 'sent'
# deltaMethod() fails with "error in t(gd) %*% vcov. : non-conformable
arguments."
deltaMethod(minimal_model, "bt2 + csent + `bt2:csent`", rhs=0)
# duplicate the dataset and change one record to be in the previously empty
cell
df_fixed <- df
df_fixed[c(13),"c"] <- 'other'
table(df_fixed$b,df_fixed$c)
#deltaMethod() now works
minimal_model_fixed <- lm(minimal_formula, data=df_fixed)
deltaMethod(minimal_model_fixed, "bt2 + csent + `bt2:csent`", rhs=0)
[[alternative HTML version deleted]]
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