[R] Metafor and forest(); not showing 'ilab' and text

Marco Colagrossi marco.colagrossi at gmail.com
Tue Sep 1 16:49:03 CEST 2015 

I did read the help(rma.mv) and I also had look at the analysis by
Konstantopoulos (2011) in the past few days. You have to apologize me
but is the first meta analysis I'm trying to carry on, it is the first
I'm working on R and moreover the terminology here is somehow
different (and confusing) with respect to the terminology I was used
in panel data analysis.

It looks to me - correct me if I'm wrong - that a model such:

     rma.mv(pc, var, random = ~ 1 | author, data=codebook)

or

     rma.mv(pc, var, random = ~ 1 | author, mods = ~ pub + SIMiv, data=codebook)

it is a varying intercept model (using Gelman-Hill Yi = Aji+BXi+Ei).
Why do you say that "Using "random = ~ 1 | author" is likely to be
insufficient. You also need to add random effects at the observation
level"? Could you please walk me through what you mean by that?

I'll (try to) explain to you what I'm doing here so you might be able
to help me out.
I'm carrying on a meta-analysis (and ultimately, few meta-regressions)
of the relationship between firm performances and bank-firm
relationship. Since I have different proxies for the latter, I
computed as effect size a raw partial correlation, a continuous
Fisher’s z-score and the one-tail p-value as a continuous
interpretation of the direction and the significance of an effect
size.

The number of studies in my meta-analysis is 29, but most of them have
multiple cases so, ultimately, I have 98 different cases. All of the
29 studies have repeated yearly observation in the same country for
different time span; let's say one from 1985 to 1991 in Spain, one
from 1987 to 1999 in China, one from 1981 to 2002 in the US and so on.
Even in case in which two different study investigates the same
country and some of the years in the time span overlaps I'm sure that
their population is drawn from different samples.

My idea was too confront what in econometrics is called a study-fixed
effect (or author fixed effect since authors have no more than one
study in my analysis), that is:

       rma(pc, var, mods = ~ I(study), data=codebook)

With a multilevel model, in order to account for the fact that
observation from the same study are not independent.

May I have your opinion on what I'm trying to do here guys?
Do you think I should take into account also a autoregressive
structure over time and correct that with struct="HAR" ?

Sorry for the long mail, I wanted to explain as better as possible,
and thank you again for your help, It is incredibly appreciated.

Marco

On 31 August 2015 at 19:28, Viechtbauer Wolfgang (STAT)
<wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
> Have you read help(rma.mv)? It describes in detail what "random = ~ 1 | author" does. Also, I think you may find some of these useful:
>
> http://www.metafor-project.org/doku.php/analyses#multivariate_multilevel_meta-analysis_models
>
> Especially: http://www.metafor-project.org/doku.php/analyses:konstantopoulos2011
>
> Using "random = ~ 1 | author" is likely to be insufficient. You also need to add random effects at the observation level.
>
> Best,
> Wolfgang
>
> --
> Wolfgang Viechtbauer, Ph.D., Statistician | Department of Psychiatry and
> Neuropsychology | Maastricht University | P.O. Box 616 (VIJV1) | 6200 MD
> Maastricht, The Netherlands | +31 (43) 388-4170 | http://www.wvbauer.com
>
>> -----Original Message-----
>> From: Marco Colagrossi [mailto:marco.colagrossi at gmail.com]
>> Sent: Monday, August 31, 2015 18:37
>> To: Michael Dewey
>> Cc: Viechtbauer Wolfgang (STAT); r-help at r-project.org
>> Subject: Re: [R] Metafor and forest(); not showing 'ilab' and text
>>
>> The solution that you proposed works perfectly, thank you very much.
>>
>> I'll wait for Wolfgang answer as I'm having few doubts about the models.
>>
>> Thanks
>>
>> On 31 August 2015 at 18:34, Michael Dewey <lists at dewey.myzen.co.uk>
>> wrote:
>> > Comments in line
>> >
>> > On 31/08/2015 16:08, Marco Colagrossi wrote:
>> >>
>> >> Thanks for your help,
>> >>
>> >> I got the mistake I was making and I managed to find a solution
>> >> regarding those graphs; I don't want to abuse of your patience but I
>> >> have three further questions:
>> >>
>> >> 1. Always regarding the forest plots, it is possible to make a
>> >> cross-subset? I try to explain my self better; I have one dummy
>> >> variable called pub and another variable called SIMiv that can take
>> >> the values of "share", "loan", "number" and "duration". How can I
>> >> subset my sample so that the forest shows only (for example) studies
>> >> when the dummy takes the value of 1 and the SIMiv variable takes the
>> >> values of "share" and "loan"?
>> >> Something like this:
>> >> forest(pc, var, ci95m, ci95p, slab = authoryear2, psize=1,
>> >> subset=(pub==1, SIMiv=("share", "loan", "duration"))
>> >>
>> >
>> > Do you not want something like
>> > (pub == 1) & (SIMIv %in% c("share", "loan", "duration"))
>> >
>> >
>> >> 2. I have few doubts regarding the multilevel modeling;
>> >>      rma.mv(pc, var, random = ~ 1 | author, data=codebook)
>> >>     if I'm correct this should be a multilevel model nested at
>> "author"
>> >> level; what I cannot understand If it is a varying intercept
>> >> (Y=A+BjX), a varying slope (Y=Aj+BX) or a varying intercept&slope
>> >> model (Y=Aj+BjX). Are there the formulas for it somewhere? So far I
>> >> only found the formulas for the estimators included in the metafor
>> >> package.
>> >>
>> >
>> > I think it a random intercept but Wolfgang may correct me there.
>> >
>> >
>> >> 3. metareg1 <- rma.mv(pc, var, random = ~ 1 | author, mods = ~ pub +
>> >> SIMiv, data=codebook)
>> >> Again, if I'm correct this should be a multilevel meta regression
>> >> (correct me if I'm wrong); I have the same doubts as before.
>> >>
>> >> Thank you again
>> >>
>> >> Marco
>> >>
>> >> On 25 August 2015 at 19:24, Michael Dewey <lists at dewey.myzen.co.uk>
>> wrote:
>> >>>
>> >>> Dear Marco
>> >>>
>> >>> When you change xlim it increases the width of the forest plot in the
>> >>> sense
>> >>> you describe. It does not push your text out of the way to make space
>> for
>> >>> it
>> >>> but instead overprints it. You may like to use alim to truncate your
>> >>> confidence interval whiskers to fit within the space you see or make
>> your
>> >>> labels shorter.
>> >>>
>> >>>
>> >>> On 25/08/2015 17:25, Marco Colagrossi wrote:
>> >>>>
>> >>>>
>> >>>> I think I've not explained myself well. When I say "the width of the
>> >>>> forest plot" I mean the region above the observed outcome, the
>> >>>> "actual" forest plot, not the plot as a whole. Even if I change
>> values
>> >>>> for Xlim, cex or ilab.xpos the width of that particular region
>> within
>> >>>> the plot doesn't change.
>> >>>>
>> >>>> Best,
>> >>>>
>> >>>> Marco
>> >>>>
>> >>>> On 25 August 2015 at 18:11, Viechtbauer Wolfgang (STAT)
>> >>>> <wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
>> >>>>>
>> >>>>>
>> >>>>> The 'xlim' argument does not change the actual width of the
>> plotting
>> >>>>> device. For that, you need to use the 'width' argument with
>> whatever
>> >>>>> device
>> >>>>> you are actually using. You can then use the 'xlim' argument to
>> create
>> >>>>> appropriate spacing to the left/right of the part of the plot that
>> >>>>> shows the
>> >>>>> estimates and their CIs. Within that space, you can then add
>> additional
>> >>>>> columns with the 'ilab' argument. It's up to you to find an
>> appropriate
>> >>>>> combination of plotting device width, character/symbol expansion
>> factor
>> >>>>> ('cex' argument), 'xlim' values, and 'ilab.xpos' values to create a
>> >>>>> nice
>> >>>>> looking plot that has no overlapping text and no excessive white
>> space.
>> >>>>> An
>> >>>>> example is this:
>> >>>>>
>> >>>>>
>> >>>>> http://www.metafor-
>> project.org/doku.php/plots:forest_plot_with_subgroups
>> >>>>>
>> >>>>> Note that it took me dozens of iterations to create that plot. You
>> just
>> >>>>> have to start experimenting.
>> >>>>>
>> >>>>> Best,
>> >>>>> Wolfgang
>> >>>>>
>> >>>>>> -----Original Message-----
>> >>>>>> From: Marco Colagrossi [mailto:marco.colagrossi at gmail.com]
>> >>>>>> Sent: Tuesday, August 25, 2015 17:59
>> >>>>>> To: Viechtbauer Wolfgang (STAT)
>> >>>>>> Cc: r-help at r-project.org; Michael Dewey
>> >>>>>> Subject: Re: [R] Metafor and forest(); not showing 'ilab' and text
>> >>>>>>
>> >>>>>> Thanks again for your help. I'm sorry to bother you but I don't
>> get
>> >>>>>> how to widen the forest plot; if I try to change the values of
>> xlim or
>> >>>>>> the ilab.xpos values the width of the forest plot region does not
>> >>>>>> change, but only moves on the graphs. What I'm I missing?
>> >>>>>>
>> >>>>>>
>> >>>>>> forest(pc, var, ci95m, ci95p, slab = authoryear, psize=1,
>> >>>>>> subset=(pub==1),
>> >>>>>>          xlim = c(-16, 6),
>> >>>>>>          ilab = data.frame(SIMdv, SIMiv),
>> >>>>>>          ilab.xpos = c(-7.5, -5.5), cex = 0.75)
>> >>>>>> op <- par(cex=.75, font=2)
>> >>>>>>         text(c(-7.5, -5.5), 54, c("DV", "IV"))
>> >>>>>>         text(-16,                54, "Author(s) and Year",
>> pos=4)
>> >>>>>>         text(6,                  54, "Outcome [95% CI]", pos=2)
>> >>>>>> par(op)
>> >>>>>>>
>> >>>>>>>
>> >>>>>>> par("usr")[1:2]
>> >>>>>>
>> >>>>>>
>> >>>>>> [1] -16   6

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