[R-meta] Does trim and fill method correct for data falsification or lower quality of small studies?

Michael Dewey ||@t@ @end|ng |rom dewey@myzen@co@uk
Wed May 4 14:17:16 CEST 2022

One might also point out that the methods has been criticised for 
detecting publicaiton bias

    author = {Schwarzer, G and Carpenter, J R and R\"ucker, G},
    title = {Empirical evaluation suggests {Copas} selection model
       preferable to trim--and--fill method for publication
       bias in meta--analysis},
    journal = {Journal of Clinical Epidemiology},
    year = {2010},
    volume = {63},
    pages = {282--288}


On 03/05/2022 23:11, towhidi wrote:
> On 2022-05-03 11:45, Viechtbauer, Wolfgang (NP) wrote:
>> Dear Ali,
>> Please see my responses below.
>> Best,
>> Wolfgang
>>> -----Original Message-----
>>> From: R-sig-meta-analysis 
>>> [mailto:r-sig-meta-analysis-bounces using r-project.org] On
>>> Behalf Of towhidi
>>> Sent: Tuesday, 03 May, 2022 1:37
>>> To: r sig meta-analysis list
>>> Subject: [R-meta] Does trim and fill method correct for data 
>>> falsification or
>>> lower quality of small studies?
>>> Dear all,
>>> The asymmetry in a funnel plot can be caused by factors other than
>>> publication bias, such as data falsification or poorer quality in
>>> smaller trials.
>> ... or unaccounted for moderators (that are correlated with study 
>> size) or more generally heterogeneity.
>>> However, the Cochrane Handbook mentions that "the trim
>>> and fill method does not take into account reasons for funnel plot
>>> asymmetry other than publication bias".
>> I searched through the handbook 
>> (https://training.cochrane.org/handbook/current) and couldn't find 
>> this quote. Where did you find this?
>>> I do not understand why it cannot account for data falsification or poor
>>> quality of small trials, assuming that these characteristics are
>>> associated with study size. For data falsification, the true observed
>>> effect size (before the fraudulent change in the data) for these studies
>>> converges on the true underlying effect size. But the falsified data
>>> move these data points to the right side, and, using the trim and fill
>>> method, this bias is neutralized by imputing their counterparts on the
>>> other side.
>> 'Neutralized' sounds a bit too optimistic. If a study is imputed 
>> corresponding to the fraudulent study (which isn't guaranteed 
>> depending on how the funnel looks in general), it is going to be 
>> placed at 'est - delta', where 'est' is the pooled estimate at the end 
>> of the trim and fill procedure and 'delta' is the distance between est 
>> and the fraudulent study. If 'est' is larger than 0, then this would 
>> still leads to some bias, but it should indeed be reduced.
>>> Of course, the confidence intervals will be biased, because
>>> we are imputing data points that do not exist (which narrows the CI) and
>>> that the bias arose from data falsification or low quality has added to
>>> the estimated sampling variance (which widens the CI). Also, it changes
>>> the weights, especially in the random-effects model.
>>> But, isn't the point estimate a corrected estimate, assuming that data
>>> falsification has caused the asymmetry?
>> I would say yes. A simulation study that has examined the properties 
>> of various methods not only when there is publication bias but also 
>> under the use of 'questionable research practices' is:
>> Carter, E. C., Schönbrodt, F. D., Gervais, W. M. & Hilgard, J. (2019). 
>> Correcting for bias in psychology: A comparison of meta-analytic 
>> methods. Advances in Methods and Practices in Psychological Science, 
>> 2(2), 115-144. https://doi.org/10.1177/2515245919847196
>>> The same argument may apply to the bias that arises from low-quality
>>> studies. However, if this is correct, I think that acknowledging this
>>> and interpreting the CIs with even more caution is more logical than
>>> assuming that the asymmetry is caused solely by publication bias and
>>> that misconduct and low quality of small studies have nothing to do with
>>> it.
>>> Is this correct? Or I am missing something?
>>> Thank you.
>>> -- 
>>> Ali Zia-Tohidi MSc
>>> Clinical Psychology
>>> University of Tehran
> Dear Wolfgang,
> Thank you for your response, and thank you for the article you mentioned.
> The quoted text, "the trim and fill method does not take into account 
> reasons for funnel plot asymmetry other than publication bias", was from 
> the previous version of the Cochrane Handbook 
> (https://handbook-5-1.cochrane.org/chapter_10/10_4_4_2_trim_and_fill.htm). 
> The trim and fill subsection is removed from the current version.
> Best,
> Ali


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