Hello,
thank you very much for your replies. I am almost done :-) but theres one
study left, where I only have sample size (not group size), mean values
and standarddeviations. Is there a way to compute cohens d from this data?
I thought it was correct to use measure="SMDH" in the escalc () function to
compute cohens d? In your illustration, Wolfgang, you use SMD as measure -
now I am confused ;-)
Thank you very much in advance!
Best,
Verena
On Tue, May 6, 2014 at 7:14 PM, Michael Dewey <i...@aghmed.fsnet.co.uk>wrote:
> At 14:23 06/05/2014, Viechtbauer Wolfgang (STAT) wrote:
>
>> Without the sample size of a study (i.e., either the group sizes or the
>> total sample size), you cannot convert the p-value to a t-value or a
>> t-value to a d-value. And for studies where you have the d-value but no
>> sample size, you cannot compute the corresponding sampling variance. So,
>> without additional information, you cannot include these studies. Maybe
>> studies where a d-value is directly reported also report a CI for the
>> d-value? Then the sampling variance can be back-calculated (since a 95% CI
>> for d is typically computed with d +- 1.96 sqrt(vi), where vi is the
>> sampling variance).
>>
>
> Verena,
> What Wolfgang says is true of course but if you have _both_ the t value
> and the p value you can backcalculate the number of degrees of freedom and
> then if you are willing to assume equal arms you have the sample sizes.
>
> finddf <- function(t, pval) {
> helper <- function(df) {res <- pval - pt(t, df, lower.tail = FALSE);
> res}
> res <- uniroot(helper, interval = c(5, 10000))
> res
> }
>
> If you call finddf with the value of t and the _one-sided_ p-value (divide
> by 2 if two-sided) it should give you a return value which, if you look at
> the element of the list called root is its estimate of the degrees of
> freedom. If you get errors from uniroot the interval supplied in the call
> may need to be widened.
>
> I would suggest that when you have your final dataset it would be a really
> good idea to do some model checks using plot.influence to see whether the
> studies for which you have imputed values are fundamentally different for
> some reason. This will also check your calculations as a bonus.
>
>
> Best,
>> Wolfgang
>>
>> > -----Original Message-----
>> > From: Verena Weinbir [mailto:vwein...@gmail.com]
>> > Sent: Tuesday, May 06, 2014 15:09
>> > To: Michael Dewey
>> > Cc: Viechtbauer Wolfgang (STAT); r-help@r-project.org
>> > Subject: Re: [R] Metafor: How to integrate effectsizes?
>> >
>> > Thank you very much for your illustration, Wolfgang! It helped me a
>> > lot.Ã And also thank you for the package-hint, Michael!
>>
>> >
>> > Now, I have re-checked the respective studies, and there still are a
>> > couple of studies left, only stating cohens d, and the respective
>> t-value
>> > and p-value - sample and group sizes are not addressed (its data from an
>> > older meta-analysis). Is there a way to embed these studies in my
>> sample?
>> > Wolfgangs illustration addresses only cases in which group sizes are
>> > stated, if I understand you correctly...
>> >
>> > Many thanks in advance,
>> >
>> > Verena
>> >
>> > On Sat, Apr 26, 2014 at 1:38 PM, Michael Dewey <i...@aghmed.fsnet.co.uk
>> >
>> > wrote:
>> > At 20:34 25/04/2014, Viechtbauer Wolfgang (STAT) wrote:
>> > If you know the d-value and the corresponding group sizes for a study,
>> > then it's possible to add that study to the rest of the dataset. Also,
>> if
>> > you only know the test statistic from an independent samples t-test (or
>> > only the p-value corresponding to that test), it's possible to back-
>> > compute what the standardized mean difference is.
>> >
>> > I added an illustration of this to the metafor package website:
>> >
>> > http://www.metafor-project.org/doku.php/tips:assembling_data_smd
>> >
>> > Verena might also like to look at the compute.es package available from
>> > CRAN to see whether any of the conversions programmed there do the job.
>> >
>> >
>> > Best,
>> > Wolfgang
>> >
>> > --
>> > Wolfgang Viechtbauer, Ph.D., Statistician
>> > Department of Psychiatry and Psychology
>> > School for Mental Health and Neuroscience
>> > Faculty of Health, Medicine, and Life Sciences
>> > Maastricht University, P.O. Box 616 (VIJV1)
>> > 6200 MD Maastricht, The Netherlands
>> > +31 (43) 388-4170Ã | http://www.wvbauer.com
>>
>> >
>> > > -----Original Message-----
>> > > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
>> > project.org]
>> > > On Behalf Of Michael Dewey
>> > > Sent: Friday, April 25, 2014 16:23
>> > > To: Verena Weinbir
>> > > Cc: r-help@r-project.org
>> > > Subject: Re: [R] Metafor: How to integrate effectsizes?
>> > >
>> > > At 12:33 25/04/2014, you wrote:
>> > > >Thank you very much for your reply and the book recommendation,
>> > Michael.
>> > > >
>> > > >Yes, I mean Cohen's d - sorry for the typo :-)
>> > > >
>> > > >Just to make this sure for me: There is no
>> > > >possibility to integrate stated Cohens' ds in an
>> > > >R-Metaanalysis (or a MA at all), if there is no
>> > > >further information traceable regarding SE or the like?
>> > >
>> > > If there is really no other information like
>> > > sample sizes, significance level, value of some
>> > > significance test then you would have to impute a
>> > > value from somewhere. That would seem a last resort.
>> > >
>> > > I have cc'ed this back to the list, please keep
>> > > it on the list so others may benefit and contribute.
>> > >
>> > >
>> > > >best regards,
>> > > >
>> > > >Verena
>> > > >
>> > > >
>> > > >On Fri, Apr 25, 2014 at 1:21 PM, Michael Dewey
>> > > ><<mailto:i...@aghmed.fsnet.co.uk>i...@aghmed.fsnet.co.uk> wrote:
>> > > >At 13:15 24/04/2014, Verena Weinbir wrote:
>> > > >Hello!
>> > > >
>> > > >I am using the metafor package for my master's thesis as an R-newbie.
>> > > While
>> > > >calculating effectsizes from my dataset (mean values and
>> > > >standarddeviations) using "escalc" shouldn't be a problem (I hope ;-
>> > )),
>> > > I
>> > > >wonder how I could at this point integrate additional studies, which
>> > > only
>> > > >state conhens d (no information about mean value and sds available),
>> > to
>> > > >calculate an overall analysis. Ãâ I would be very grateful for your
>>
>> > > support!
>> > > >
>> > > >
>> > > >You mean Cohen's d I think.
>> > > >
>> > > >You will need some more information to enable
>> > > >you to calculate its standard error. Have a look at Rosenthal's
>> > chapter
>> > > in
>> > > >@book{cooper94,
>> > > >Ãâ Ã Ãâ author = {Cooper, H and Hedges, L V},
>> > > >Ãâ Ã Ãâ title = {A handbook of research synthesis},
>> > > >Ãâ Ã Ãâ year = {1994},
>> > > >Ãâ Ã Ãâ publisher = {Russell Sage},
>> > > >Ãâ Ã Ãâ address = {New York},
>> > > >Ãâ Ã Ãâ keywords = {meta-analysis}
>>
>> > > >}
>> > > >(There is an updated edition)
>> > > >This gives you more information about converting
>> > > >effect sizes and extracting them from unpromising beginnings.
>> > > >
>> > > >It often requires some ingenuity to get the
>> > > >information you need so have a go and then get
>> > > >back here with more details if you run into problems
>> > > >
>> > > >
>> > > >Best regards,
>> > > >
>> > > >Verena
>>
>
> Michael Dewey
> i...@aghmed.fsnet.co.uk
> http://www.aghmed.fsnet.co.uk/home.html
>
>
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
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.
