[R-meta] meta-regression: categorical

Hi Everybody,

I have a new question about meta-regression.
My database consists only of factors (no characters), so I suppose I do not
need 'factor()' in 'mods', i.e. 'mods = ~ factor-var'. I also tried 'mods =
~ factor(factor-var)' and I receive the same results as expected.
Only, there is one difference, 'mods = ~ factor-var' gives a warning
message:
*"In rma(measure = "SMCC", yi = yi, vi = vi, data = datsub, digits = 2,  :*
*  Redundant predictors dropped from the model."*
Whereas 'mods = ~ factor(factor-var)' does not give this message. What is
the reason for this?

So, my question is not why I receive this message, but why the difference:
with/out warning message.

Best regards,
Roberto
PS the same happens with a character variable: i.e. 'mods = ~ chr-var' as
well as 'mods = ~ factor(chr-var)'.

Op do 26 apr. 2018 om 07:42 schreef P. Roberto Bakker <
robertobakker at gmail.com>:

Hi Wolfgang,

Thank you for your information and explanation.

Bw Roberto

2018-04-24 12:25 GMT+02:00 Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer at maastrichtuniversity.nl>:

Hi Roberto,

If you put a character variable (or a factor) into a formula, it is
automatically dummy coded. Actually, the type of coding depends on:

options("contrasts")

But the default for that is:

         unordered           ordered
"contr.treatment"      "contr.poly"

And help(contr.treatment) explains what kind of coding this is, namely
the 'usual' dummy coding where one level is the 'reference' level (and
whose dummy gets omitted).

Best,
Wolfgang

-----Original Message-----
From: R-sig-meta-analysis [mailto:
r-sig-meta-analysis-bounces at r-project.org] On Behalf Of P. Roberto Bakker
Sent: Tuesday, 24 April, 2018 11:14
To: r-sig-meta-analysis at r-project.org
Subject: [R-meta] meta-regression: categorical

Hi everybody,

In:
http://www.metafor-project.org/doku.php/analyses:vanhouwelingen2002
'allocation' is put in syntax without dummy coding

rma <http://finzi.psych.upenn.edu/library/metafor/html/rma.uni.html>(yi,
vi, mods = ~ alloc, data
<http://stat.ethz.ch/R-manual/R-devel/library/utils/html/data.html>=dat,
method="ML")

If I am not wrong, 'allocation' is a catergorical variabel, and I suppose
the R handles the coding of dummy automatically.
Correct?

I found this information in:
https://cran.r-project.org/web/packages/metafor/metafor.pdf
*Categorical moderator variables can be included in the model via the mods
argument in the same way that appropriately (dummy) coded categorical
independent variables can be included in linear models. One can either do
the dummy coding manually or use a model formula together with the factor
function to let R handle the coding automatically.   *

*Best wishes and thank you in advance*
*Roberto*

	[[alternative HTML version deleted]]

Dear Roberto

I suspect the answer is that your original factor variable has levels
which do not appear in your data-set so they are dropped when the model
matrix is formed.

If you do factor(already_existing_factor) it silently drops the levels.
This is rather hidden in the documentation as the second paragraph of Value

Michael

On 06/01/2020 09:27, P. Roberto Bakker wrote:

Hi Everybody,

I have a new question about meta-regression.
My database consists only of factors (no characters), so I suppose I do

not

need 'factor()' in 'mods', i.e. 'mods = ~ factor-var'. I also tried

'mods =

~ factor(factor-var)' and I receive the same results as expected.
Only, there is one difference, 'mods = ~ factor-var' gives a warning
message:
*"In rma(measure = "SMCC", yi = yi, vi = vi, data = datsub, digits = 2,

:*

*  Redundant predictors dropped from the model."*
Whereas 'mods = ~ factor(factor-var)' does not give this message. What is
the reason for this?

So, my question is not why I receive this message, but why the

difference:

with/out warning message.

Best regards,
Roberto
PS the same happens with a character variable: i.e. 'mods = ~ chr-var' as
well as 'mods = ~ factor(chr-var)'.

Op do 26 apr. 2018 om 07:42 schreef P. Roberto Bakker <
robertobakker at gmail.com>:

Hi Wolfgang,

Thank you for your information and explanation.

Bw Roberto

2018-04-24 12:25 GMT+02:00 Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer at maastrichtuniversity.nl>:

Hi Roberto,

If you put a character variable (or a factor) into a formula, it is
automatically dummy coded. Actually, the type of coding depends on:

options("contrasts")

But the default for that is:

         unordered           ordered
"contr.treatment"      "contr.poly"

And help(contr.treatment) explains what kind of coding this is, namely
the 'usual' dummy coding where one level is the 'reference' level (and
whose dummy gets omitted).

Best,
Wolfgang

-----Original Message-----
From: R-sig-meta-analysis [mailto:
r-sig-meta-analysis-bounces at r-project.org] On Behalf Of P. Roberto

Bakker

Sent: Tuesday, 24 April, 2018 11:14
To: r-sig-meta-analysis at r-project.org
Subject: [R-meta] meta-regression: categorical

Hi everybody,

In:
http://www.metafor-project.org/doku.php/analyses:vanhouwelingen2002
'allocation' is put in syntax without dummy coding

rma <http://finzi.psych.upenn.edu/library/metafor/html/rma.uni.html

(yi,

vi, mods = ~ alloc, data
<http://stat.ethz.ch/R-manual/R-devel/library/utils/html/data.html

=dat,

method="ML")

If I am not wrong, 'allocation' is a catergorical variabel, and I

suppose

the R handles the coding of dummy automatically.
Correct?

I found this information in:
https://cran.r-project.org/web/packages/metafor/metafor.pdf
*Categorical moderator variables can be included in the model via the

mods

argument in the same way that appropriately (dummy) coded categorical
independent variables can be included in linear models. One can either

do

the dummy coding manually or use a model formula together with the

factor

function to let R handle the coding automatically.   *

*Best wishes and thank you in advance*
*Roberto*

      [[alternative HTML version deleted]]

--
Michael
http://www.dewey.myzen.co.uk/home.html