[R] Regression and Sub-Groups Analysis in Metafor

Tue May 31 22:52:56 CEST 2016

Thank you, Bert.  That's perfect!  I will do.
On 31 May 2016 21:43, "Bert Gunter" <bgunter.4567 at gmail.com> wrote:

> Briefly, as this is off-topic, and inline:
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along
> and sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
>
> On Tue, May 31, 2016 at 11:32 AM, Dan Kolubinski <kolubind at lsbu.ac.uk>
> wrote:
> > That makes perfect sense.  Thank you, Michael.  I take your point about
> not
> > chasing the data and definitely see the risks involved in doing so.  Our
> > hypothesis was that the first, second and fourth variables would be
> > significant, but the third one (intervention) would not be.
>
> That is **not** a legitimate scientific hypothesis. Post to a
> statistical list like stats.stackexchange.com to learn why not.
>
> Cheers,
> Bert
>
>
>
>  I will
> > double-check the dataset to make sure that there are not any errors and
> > will report the results as we see them.  I much appreciate you taking the
> > time!
> >
> > Best wishes,
> > Dan
> >
> > On Tue, May 31, 2016 at 12:02 PM, Michael Dewey <lists at dewey.myzen.co.uk
> >
> > wrote:
> >
> >> In-line
> >>
> >> On 30/05/2016 19:27, Dan Kolubinski wrote:
> >>
> >>> I am completing a meta-analysis on the effect of CBT on low self-esteem
> >>> and
> >>> I could use some help regarding the regression feature in metafor.
> Based
> >>> on the studies that I am using for the analysis, I identified 4
> potential
> >>> moderators that I want to explore:
> >>> - Some of the studies that I am using used RCTs to compare an
> intervention
> >>> with a waitlist and others used the pre-score as the control in a
> >>> single-group design.
> >>> - Some of the groups took place in one day and others took several
> weeks.
> >>> - There are three discernible interventions being represented
> >>> - The initial level of self-esteem varies
> >>>
> >>> Based on the above, I used this command to conduct a meta-analysis
> using
> >>> standarized mean differences:
> >>>
> >>>
> >>>
> >>> MetaMod<-rma(m1i=m1, m2i=m2, sd1i=sd1, sd2i=sd2, n1i=n1, n2i=n2,
> >>> mods=cbind(dur, rct, int, level),measure = "SMD")
> >>>
> >>>
> >> You could also say mods = ~ dur + rct + int + level
> >>
> >>
> >>>
> >>> Would this be the best command to use for what I described?  Also, what
> >>> could I add to the command so that the forest plot shows a sub-group
> >>> analysis using the 'dur' variable as a between-groups distinction?
> >>>
> >>>
> >> You have to adjust the forest plot by hand and then use add.polygon to
> >> add the summaries for each level of dur.
> >>
> >>
> >>> Also, with respect to the moderators, this is what was delivered:
> >>>
> >>>
> >>>
> >>> Test of Moderators (coefficient(s) 2,3,4,5):
> >>> QM(df = 4) = 8.7815, p-val = 0.0668
> >>>
> >>> Model Results:
> >>>
> >>>          estimate      se     zval    pval    ci.lb   ci.ub
> >>> intrcpt    0.7005  0.6251   1.1207  0.2624  -0.5246  1.9256
> >>> dur        0.5364  0.2411   2.2249  0.0261   0.0639  1.0090  *
> >>> rct       -0.3714  0.1951  -1.9035  0.0570  -0.7537  0.0110  .
> >>> int        0.0730  0.1102   0.6628  0.5075  -0.1430  0.2890
> >>> level     -0.2819  0.2139  -1.3180  0.1875  -0.7010  0.1373
> >>>
> >>> ---
> >>> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> >>>
> >>>
> >>>
> >> So the totality of moderators did not reach an arbitrary level of
> >> significance.
> >>
> >>
> >>> From this, can I interpret that the variable 'dur' (duration of
> >>>>
> >>> intervention) has a significant effect and the variable 'rct' (whether
> a
> >>> study was an RCT or used pre-post scores) was just shy of being
> >>> statistically significant?  I mainly ask, because the QM-score has a
> >>> p-value of 0.0668, which I thought would mean that none of the
> moderators
> >>> would be significant.  Would I be better off just listing one or two
> >>> moderators instead of four?
> >>>
> >>>
> >> At the moment you get an overall test of the moderators which you had a
> >> scientific reason for using. If you start selecting based on the data
> >> you run the risk of ending up with confidence intervals and significance
> >> levels which do not have the meaning they are supposed to have.
> >>
> >>
> >> Much appreciated,
> >>> Dan
> >>>
> >>>       [[alternative HTML version deleted]]
> >>>
> >>> ______________________________________________
> >>> R-help at 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.
> >>>
> >>>
> >> --
> >> Michael
> >> http://www.dewey.myzen.co.uk/home.html
> >>
> >
> >         [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help at 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.
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