define subset argument for function lm as variable?

Hi

I want to do a series of linear models, and would like to define the input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in a
variable. My reasoning is, that I have the subset in the results object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated immediately. Is
is it possible to do what I want to do here, or do I have to go back to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model, where
year is the
dat.lme <- lme(
             fixed = feff,                           # fixed effect in the
model
             data  = dat,
             random = reff,                          # random effect in the
model
             correlation = corAR1(form=~year|plant), #
             subset = dead==FALSE & recTreat==FALSE, #
             na.action = na.omit
             )
dat.lm <- lm(
            formula =  feff,              # fixed effect in the model
            data = dat,
            subset = dead==FALSE & recTreat==FALSE,
            na.action = na.omit
            )

Thanks,

Rainer

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

Hi

I want to do a series of linear models, and would like to define the input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in a
variable. My reasoning is, that I have the subset in the results object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated immediately. Is
is it possible to do what I want to do here, or do I have to go back to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model, where
year is the
dat.lme <- lme(
             fixed = feff,                           # fixed effect in the
model
             data  = dat,
             random = reff,                          # random effect in the
model
             correlation = corAR1(form=~year|plant), #
             subset = dead==FALSE & recTreat==FALSE, #
             na.action = na.omit
             )
dat.lm <- lm(
            formula =  feff,              # fixed effect in the model
            data = dat,
            subset = dead==FALSE & recTreat==FALSE,
            na.action = na.omit
            )

Thanks,

Rainer

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

?? I do not groc what you mean. ... subset == subs would work fine in
your lm call. So unless someone else does get it, you may need to
elaborate.

In general, ?substitute, ?bquote, and ?quote are useful to avoid
immediate evaluation of calls, but I don't know if that's relevant to
what you want here.

-- Bert

On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com> wrote:

Hi

I want to do a series of linear models, and would like to define the input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in a
variable. My reasoning is, that I have the subset in the results object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated immediately. Is
is it possible to do what I want to do here, or do I have to go back to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model, where
year is the
dat.lme <- lme(
              fixed = feff,                           # fixed effect in the
model
              data  = dat,
              random = reff,                          # random effect in the
model
              correlation = corAR1(form=~year|plant), #
              subset = dead==FALSE & recTreat==FALSE, #
              na.action = na.omit
              )
dat.lm <- lm(
             formula =  feff,              # fixed effect in the model
             data = dat,
             subset = dead==FALSE & recTreat==FALSE,
             na.action = na.omit
             )

Thanks,

Rainer

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

On 21/08/12 16:57, Bert Gunter wrote:

?? I do not groc what you mean. ... subset == subs would work fine in
your lm call. So unless someone else does get it, you may need to
elaborate.

OK - here is an example:

dat <- data.frame(
         ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14),
         trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69),
         group = gl(2,10,20, labels=c("Ctl","Trt")),
         weight = c(ctl, trt)
         )
lm(weight ~ group, data=dat, subset=trt>0)

subst <- trt>0 ### here I get the obvious error: Error: object 'trt' not
found

# I want to use:

lm(weight ~ group, data=dat, subset=subst)

In general, ?substitute, ?bquote, and ?quote are useful to avoid
immediate evaluation of calls, but I don't know if that's relevant to
what you want here.

Looks promising from the help, but I don't get it to work.

Rainer

-- Bert

On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com>
wrote:

Hi

I want to do a series of linear models, and would like to define the
input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in a
variable. My reasoning is, that I have the subset in the results object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated
immediately. Is
is it possible to do what I want to do here, or do I have to go back
to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model,
where
year is the
dat.lme <- lme(
              fixed = feff,                           # fixed effect
in the
model
              data  = dat,
              random = reff,                          # random effect
in the
model
              correlation = corAR1(form=~year|plant), #
              subset = dead==FALSE & recTreat==FALSE, #
              na.action = na.omit
              )
dat.lm <- lm(
             formula =  feff,              # fixed effect in the model
             data = dat,
             subset = dead==FALSE & recTreat==FALSE,
             na.action = na.omit
             )

Thanks,

Rainer

-- 
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation
Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

Hi Rainer,
I got an error while replicating your data.frame construction.

But this worked for me

ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
dat <- data.frame( group = gl(2,10,20, labels=c("Ctl","Trt")),
          weight = c(ctl, trt)
          )

lm(weight ~ group, data=dat, subset=trt>0)

Cheers

Am 21.08.2012 17:11, schrieb Rainer M Krug:

On 21/08/12 16:57, Bert Gunter wrote:

?? I do not groc what you mean. ... subset == subs would work fine in
your lm call. So unless someone else does get it, you may need to
elaborate.

OK - here is an example:

dat <- data.frame(
          ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14),
          trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69),
          group = gl(2,10,20, labels=c("Ctl","Trt")),
          weight = c(ctl, trt)
          )
lm(weight ~ group, data=dat, subset=trt>0)

subst <- trt>0 ### here I get the obvious error: Error: object 'trt' not
found

# I want to use:

lm(weight ~ group, data=dat, subset=subst)

In general, ?substitute, ?bquote, and ?quote are useful to avoid
immediate evaluation of calls, but I don't know if that's relevant to
what you want here.

Looks promising from the help, but I don't get it to work.

Rainer

-- Bert

On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com>
wrote:

Hi

I want to do a series of linear models, and would like to define the
input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in a
variable. My reasoning is, that I have the subset in the results object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated
immediately. Is
is it possible to do what I want to do here, or do I have to go back
to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model,
where
year is the
dat.lme <- lme(
               fixed = feff,                           # fixed effect
in the
model
               data  = dat,
               random = reff,                          # random effect
in the
model
               correlation = corAR1(form=~year|plant), #
               subset = dead==FALSE & recTreat==FALSE, #
               na.action = na.omit
               )
dat.lm <- lm(
              formula =  feff,              # fixed effect in the model
              data = dat,
              subset = dead==FALSE & recTreat==FALSE,
              na.action = na.omit
              )

Thanks,

Rainer

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation
Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

On 21/08/12 17:35, Eik Vettorazzi wrote:

Hi Rainer,
I got an error while replicating your data.frame construction.

But this worked for me

ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
dat <- data.frame( group = gl(2,10,20, labels=c("Ctl","Trt")),
          weight = c(ctl, trt)
          )

Sorry  - to much garbage in my workspace left.

Just add:

rm(ctl)
rm(trt)

after the definition

lm(weight ~ group, data=dat, subset=trt>0)

this obviously works, but I would like to have:

subst <- trt>0

lm(weight ~ group, data=dat, subset=subst)

Sorry about this,

Rainer

Cheers

Am 21.08.2012 17:11, schrieb Rainer M Krug:

On 21/08/12 16:57, Bert Gunter wrote:

?? I do not groc what you mean. ... subset == subs would work fine in
your lm call. So unless someone else does get it, you may need to
elaborate.

OK - here is an example:

dat <- data.frame(
          ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14),
          trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69),
          group = gl(2,10,20, labels=c("Ctl","Trt")),
          weight = c(ctl, trt)
          )
lm(weight ~ group, data=dat, subset=trt>0)

subst <- trt>0 ### here I get the obvious error: Error: object 'trt' not
found

# I want to use:

lm(weight ~ group, data=dat, subset=subst)

In general, ?substitute, ?bquote, and ?quote are useful to avoid
immediate evaluation of calls, but I don't know if that's relevant to
what you want here.

Looks promising from the help, but I don't get it to work.

Rainer

-- Bert

On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com>
wrote:

Hi

I want to do a series of linear models, and would like to define the
input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in
a
variable. My reasoning is, that I have the subset in the results
object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated
immediately. Is
is it possible to do what I want to do here, or do I have to go back
to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model,
where
year is the
dat.lme <- lme(
               fixed = feff,                           # fixed effect
in the
model
               data  = dat,
               random = reff,                          # random effect
in the
model
               correlation = corAR1(form=~year|plant), #
               subset = dead==FALSE & recTreat==FALSE, #
               na.action = na.omit
               )
dat.lm <- lm(
              formula =  feff,              # fixed effect in the model
              data = dat,
              subset = dead==FALSE & recTreat==FALSE,
              na.action = na.omit
              )

Thanks,

Rainer

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation
Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

What is wrong with what I suggested initially?

subst <- expression(trt > 0)
lm(weight ~ group, data=dat, subset=eval(subst))

??

On Tue, Aug 21, 2012 at 8:41 AM, Rainer M Krug <r.m.krug at gmail.com> wrote:

On 21/08/12 17:35, Eik Vettorazzi wrote:

Hi Rainer,
I got an error while replicating your data.frame construction.

But this worked for me

ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
dat <- data.frame( group = gl(2,10,20, labels=c("Ctl","Trt")),
           weight = c(ctl, trt)
           )

Sorry  - to much garbage in my workspace left.

Just add:

rm(ctl)
rm(trt)

after the definition

lm(weight ~ group, data=dat, subset=trt>0)

this obviously works, but I would like to have:

subst <- trt>0

lm(weight ~ group, data=dat, subset=subst)

Sorry about this,

Rainer

Cheers

Am 21.08.2012 17:11, schrieb Rainer M Krug:

On 21/08/12 16:57, Bert Gunter wrote:

?? I do not groc what you mean. ... subset == subs would work fine in
your lm call. So unless someone else does get it, you may need to
elaborate.

OK - here is an example:

dat <- data.frame(
           ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14),
           trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69),
           group = gl(2,10,20, labels=c("Ctl","Trt")),
           weight = c(ctl, trt)
           )
lm(weight ~ group, data=dat, subset=trt>0)

subst <- trt>0 ### here I get the obvious error: Error: object 'trt' not
found

# I want to use:

lm(weight ~ group, data=dat, subset=subst)

In general, ?substitute, ?bquote, and ?quote are useful to avoid
immediate evaluation of calls, but I don't know if that's relevant to
what you want here.

Looks promising from the help, but I don't get it to work.

Rainer

-- Bert

On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com>
wrote:

Hi

I want to do a series of linear models, and would like to define the
input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in
a
variable. My reasoning is, that I have the subset in the results
object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated
immediately. Is
is it possible to do what I want to do here, or do I have to go back
to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model,
where
year is the
dat.lme <- lme(
                fixed = feff,                           # fixed effect
in the
model
                data  = dat,
                random = reff,                          # random effect
in the
model
                correlation = corAR1(form=~year|plant), #
                subset = dead==FALSE & recTreat==FALSE, #
                na.action = na.omit
                )
dat.lm <- lm(
               formula =  feff,              # fixed effect in the model
               data = dat,
               subset = dead==FALSE & recTreat==FALSE,
               na.action = na.omit
               )

Thanks,

Rainer

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation
Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

On 21/08/12 17:35, Eik Vettorazzi wrote:

Hi Rainer,
I got an error while replicating your data.frame construction.

But this worked for me

ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
dat <- data.frame( group = gl(2,10,20, labels=c("Ctl","Trt")),
          weight = c(ctl, trt)
          )

Sorry  - to much garbage in my workspace left.

Just add:

rm(ctl)
rm(trt)

after the definition

lm(weight ~ group, data=dat, subset=trt>0)

this obviously works, but I would like to have:

subst <- trt>0
lm(weight ~ group, data=dat, subset=subst)

Sorry about this,

Rainer

Cheers

Am 21.08.2012 17:11, schrieb Rainer M Krug:

On 21/08/12 16:57, Bert Gunter wrote:

?? I do not groc what you mean. ... subset == subs would work fine in
your lm call. So unless someone else does get it, you may need to
elaborate.

OK - here is an example:

dat <- data.frame(
          ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14),
          trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69),
          group = gl(2,10,20, labels=c("Ctl","Trt")),
          weight = c(ctl, trt)
          )
lm(weight ~ group, data=dat, subset=trt>0)

subst <- trt>0 ### here I get the obvious error: Error: object 'trt' not
found

# I want to use:

lm(weight ~ group, data=dat, subset=subst)

In general, ?substitute, ?bquote, and ?quote are useful to avoid
immediate evaluation of calls, but I don't know if that's relevant to
what you want here.

Looks promising from the help, but I don't get it to work.

Rainer

-- Bert

On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com>
wrote:

Hi

I want to do a series of linear models, and would like to define the
input
arguments for lm() as variables. I managed easily to define the
formula
arguments in a variable, but I also would like to have the "subset"
in a
variable. My reasoning is, that I have the subset in the results
object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated
immediately. Is
is it possible to do what I want to do here, or do I have to go back
to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model,
where
year is the
dat.lme <- lme(
               fixed = feff,                           # fixed effect
in the
model
               data  = dat,
               random = reff,                          # random effect
in the
model
               correlation = corAR1(form=~year|plant), #
               subset = dead==FALSE & recTreat==FALSE, #
               na.action = na.omit
               )
dat.lm <- lm(
              formula =  feff,              # fixed effect in the
model
              data = dat,
              subset = dead==FALSE & recTreat==FALSE,
              na.action = na.omit
              )

Thanks,

Rainer

-- 
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation
Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

On 21/08/12 17:54, Joshua Wiley wrote:

What is wrong with what I suggested initially?

subst <- expression(trt > 0)
lm(weight ~ group, data=dat, subset=eval(subst))

That it does not work?

ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
dat <- data.frame( group = gl(2,10,20, labels=c("Ctl","Trt")),
          weight = c(ctl, trt)
          )
rm(ctl)
rm(trt)
subst <- expression(trt > 0)
lm(weight ~ group, data=dat, subset=eval(subst))
# output: Error in eval(expr, envir, enclos) : object 'trt' not found


and

lm(weight ~ group, data=dat, subset=subst)
# output: Error in xj[i] : invalid subscript type 'expression'

 >

also does not work.

Rainer

??

On Tue, Aug 21, 2012 at 8:41 AM, Rainer M Krug <r.m.krug at gmail.com> wrote:

On 21/08/12 17:35, Eik Vettorazzi wrote:

Hi Rainer,
I got an error while replicating your data.frame construction.

But this worked for me

ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
dat <- data.frame( group = gl(2,10,20, labels=c("Ctl","Trt")),
           weight = c(ctl, trt)
           )

Sorry  - to much garbage in my workspace left.

Just add:

rm(ctl)
rm(trt)

after the definition

lm(weight ~ group, data=dat, subset=trt>0)

this obviously works, but I would like to have:

subst <- trt>0

lm(weight ~ group, data=dat, subset=subst)

Sorry about this,

Rainer

Cheers

Am 21.08.2012 17:11, schrieb Rainer M Krug:

On 21/08/12 16:57, Bert Gunter wrote:

?? I do not groc what you mean. ... subset == subs would work fine in
your lm call. So unless someone else does get it, you may need to
elaborate.

OK - here is an example:

dat <- data.frame(
           ctl = c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14),
           trt = c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69),
           group = gl(2,10,20, labels=c("Ctl","Trt")),
           weight = c(ctl, trt)
           )
lm(weight ~ group, data=dat, subset=trt>0)

subst <- trt>0 ### here I get the obvious error: Error: object 'trt' not
found

# I want to use:

lm(weight ~ group, data=dat, subset=subst)

In general, ?substitute, ?bquote, and ?quote are useful to avoid
immediate evaluation of calls, but I don't know if that's relevant to
what you want here.

Looks promising from the help, but I don't get it to work.

Rainer

-- Bert

On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com>
wrote:

Hi

I want to do a series of linear models, and would like to define the
input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in
a
variable. My reasoning is, that I have the subset in the results
object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated
immediately. Is
is it possible to do what I want to do here, or do I have to go back
to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model,
where
year is the
dat.lme <- lme(
                fixed = feff,                           # fixed effect
in the
model
                data  = dat,
                random = reff,                          # random effect
in the
model
                correlation = corAR1(form=~year|plant), #
                subset = dead==FALSE & recTreat==FALSE, #
                na.action = na.omit
                )
dat.lm <- lm(
               formula =  feff,              # fixed effect in the model
               data = dat,
               subset = dead==FALSE & recTreat==FALSE,
               na.action = na.omit
               )

Thanks,

Rainer

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation
Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

Hi Rainer,

You could try:

subs <- expression(dead==FALSE & recTreat==FALSE)

lme(formula, subset = eval(subs))

Not tested, but something along those lines should work.

Josh

On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com> wrote:

Hi

I want to do a series of linear models, and would like to define the input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in a
variable. My reasoning is, that I have the subset in the results object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated immediately. Is
is it possible to do what I want to do here, or do I have to go back to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model, where
year is the
dat.lme <- lme(
             fixed = feff,                           # fixed effect in the
model
             data  = dat,
             random = reff,                          # random effect in the
model
             correlation = corAR1(form=~year|plant), #
             subset = dead==FALSE & recTreat==FALSE, #
             na.action = na.omit
             )
dat.lm <- lm(
            formula =  feff,              # fixed effect in the model
            data = dat,
            subset = dead==FALSE & recTreat==FALSE,
            na.action = na.omit
            )

Thanks,

Rainer

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

Le mardi 21 ao?t 2012 ? 07:51 -0700, Joshua Wiley a ?crit :

Hi Rainer,

You could try:

subs <- expression(dead==FALSE & recTreat==FALSE)

lme(formula, subset = eval(subs))

Not tested, but something along those lines should work.

Out of curiosity, why isn't "subset" (and "weights", which is very
similar in that regard) evaluated in the "data" environment, just like
the formula? Is this for historical reasons, or are there drawbacks to
such a feature?

It seems very common to pass a data frame via the "data" argument, and
use variables from it for subsetting and/or weighting.


Regards

Josh

On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com> wrote:

Hi

I want to do a series of linear models, and would like to define the input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in a
variable. My reasoning is, that I have the subset in the results object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated immediately. Is
is it possible to do what I want to do here, or do I have to go back to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model, where
year is the
dat.lme <- lme(
             fixed = feff,                           # fixed effect in the
model
             data  = dat,
             random = reff,                          # random effect in the
model
             correlation = corAR1(form=~year|plant), #
             subset = dead==FALSE & recTreat==FALSE, #
             na.action = na.omit
             )
dat.lm <- lm(
            formula =  feff,              # fixed effect in the model
            data = dat,
            subset = dead==FALSE & recTreat==FALSE,
            na.action = na.omit
            )

Thanks,

Rainer

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

On Wed, Aug 29, 2012 at 3:56 AM, Milan Bouchet-Valat <nalimilan at club.fr> wrote:

Le mardi 21 ao?t 2012 ? 07:51 -0700, Joshua Wiley a ?crit :

Hi Rainer,

You could try:

subs <- expression(dead==FALSE & recTreat==FALSE)

lme(formula, subset = eval(subs))

Not tested, but something along those lines should work.

Out of curiosity, why isn't "subset" (and "weights", which is very
similar in that regard) evaluated in the "data" environment, just like
the formula? Is this for historical reasons, or are there drawbacks to
such a feature?

I am not sure about weights offhand, but subset is evaluated in the
data environment----that is why that solution works.  The original
question was how to setup the expression as an object that was passed
to subset.  The trick is to avoid having the logical expression
evaluated when the object is created, which I avoided by using
expression, and then in lme() forcing the evaluation of the object.

It seems very common to pass a data frame via the "data" argument, and
use variables from it for subsetting and/or weighting.


Regards

Josh

On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com> wrote:

Hi

I want to do a series of linear models, and would like to define the input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in a
variable. My reasoning is, that I have the subset in the results object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated immediately. Is
is it possible to do what I want to do here, or do I have to go back to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model, where
year is the
dat.lme <- lme(
             fixed = feff,                           # fixed effect in the
model
             data  = dat,
             random = reff,                          # random effect in the
model
             correlation = corAR1(form=~year|plant), #
             subset = dead==FALSE & recTreat==FALSE, #
             na.action = na.omit
             )
dat.lm <- lm(
            formula =  feff,              # fixed effect in the model
            data = dat,
            subset = dead==FALSE & recTreat==FALSE,
            na.action = na.omit
            )

Thanks,

Rainer

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug

Le mercredi 29 ao?t 2012 ? 04:01 -0700, Joshua Wiley a ?crit :

On Wed, Aug 29, 2012 at 3:56 AM, Milan Bouchet-Valat <nalimilan at club.fr> wrote:

Le mardi 21 ao?t 2012 ? 07:51 -0700, Joshua Wiley a ?crit :

Hi Rainer,

You could try:

subs <- expression(dead==FALSE & recTreat==FALSE)

lme(formula, subset = eval(subs))

Not tested, but something along those lines should work.

Out of curiosity, why isn't "subset" (and "weights", which is very
similar in that regard) evaluated in the "data" environment, just like
the formula? Is this for historical reasons, or are there drawbacks to
such a feature?

I am not sure about weights offhand, but subset is evaluated in the
data environment----that is why that solution works.  The original
question was how to setup the expression as an object that was passed
to subset.  The trick is to avoid having the logical expression
evaluated when the object is created, which I avoided by using
expression, and then in lme() forcing the evaluation of the object.

OK, my phrasing was not really correct. What I meant (and what triggered
the OP question) was : why doesn't the "subset" argument behave the same
in lm() and in subset.data.frame()? Is there any advantage to evaluating
the argument at the object creation?

AFAICS, subset.data.frame() merely uses this trick:
e <- substitute(subset)
r <- eval(e, x, parent.frame())


I'm probably missing something... ;-)

It seems very common to pass a data frame via the "data" argument, and
use variables from it for subsetting and/or weighting.


Regards

Josh

On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com> wrote:

Hi

I want to do a series of linear models, and would like to define the input
arguments for lm() as variables. I managed easily to define the formula
arguments in a variable, but I also would like to have the "subset" in a
variable. My reasoning is, that I have the subset in the results object.

So I wiould like to add a line like:

subs <- dead==FALSE & recTreat==FALSE

which obviously does not work as the expression is evaluated immediately. Is
is it possible to do what I want to do here, or do I have to go back to use

dat <- subset(dat, dead==FALSE & recTreat==FALSE)

?



dat <- loadSPECIES(SPECIES)
feff <- height~pHarv*year               # fixed effect in the model
reff <- ~year|plant                     # random effect in the model, where
year is the
dat.lme <- lme(
             fixed = feff,                           # fixed effect in the
model
             data  = dat,
             random = reff,                          # random effect in the
model
             correlation = corAR1(form=~year|plant), #
             subset = dead==FALSE & recTreat==FALSE, #
             na.action = na.omit
             )
dat.lm <- lm(
            formula =  feff,              # fixed effect in the model
            data = dat,
            subset = dead==FALSE & recTreat==FALSE,
            na.action = na.omit
            )

Thanks,

Rainer

--
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

Centre of Excellence for Invasion Biology
Stellenbosch University
South Africa

Tel :       +33 - (0)9 53 10 27 44
Cell:       +33 - (0)6 85 62 59 98
Fax :       +33 - (0)9 58 10 27 44

Fax (D):    +49 - (0)3 21 21 25 22 44

email:      Rainer at krugs.de

Skype:      RMkrug