[R-meta] multiple correlation meta-analysis as in Cheung & Chan (2002)

[Catia Oliveira]

Oh, I didn't realize. You cite it in one of your papers so I just assumed
it had been written by you as well. I apologise for the mistake.

On Sun, Jan 15, 2023, 3:13 AM Mike Cheung <mikewlcheung using gmail.com> wrote:

> Dear Catia,
>
> I see.It was written by Shu Fai Cheung, not Mike Cheung.
>
> https://www.researchgate.net/publication/331113383_The_role_of_perceived_behavioral_control_in_predicting_human_behavior_A_meta-analytic_review_of_studies_on_the_theory_of_planned_behavior
>
> Mike
>
> On Sun, Jan 15, 2023 at 10:50 AM Catia Oliveira <catia.oliveira using york.ac.uk>
> wrote:
>
>> I'm referring to the paper with Chan from 2000, this is an unpublished
>> paper. I indicated the wrong date in the title.
>>
>> On Sun, Jan 15, 2023, 2:43 AM Mike Cheung <mikewlcheung using gmail.com> wrote:
>>
>>> Dear Catia,
>>>
>>> I am afraid I did not get your questions, as something was wrong here.
>>>
>>> The study you mentioned neither used multiple correlations as the effect
>>> sizes nor Hunter and Schmidt's approach. It used correlation matrices as
>>> inputs to fit a customized meta-analytic structural equation modeling
>>> (MASEM) to handle interactions.
>>>
>>> The complete data and R code are available at https://osf.io/3w2k7/ for
>>> reproducibility.
>>>
>>> Best,
>>> Mike
>>>
>>> On Thu, Jan 12, 2023 at 10:47 PM Catia Oliveira <
>>> catia.oliveira using york.ac.uk> wrote:
>>>
>>>> Hello,
>>>>
>>>> I am interested in running a similar study to that conducted by Mike
>>>> Cheung (The role of perceived behavioral control in predicting human
>>>> behavior: A
>>>> meta-analytic review of studies on the theory of planned behavior)
>>>> where the multiple correlations estimates (square root of R2) were
>>>> tracked to determine whether a set of predictors have explanatory
>>>> power when one has been accounted for. This will be done across
>>>> datasets, so I would have to pool all the multiple correlations
>>>> estimates using the same variables (e.g. all studies with 2 predictors
>>>> X ~ A + B and all studies with 3 predictors X ~ A + B + C). Could I
>>>> still use the Hunter and Schmidt approach used by Mike Cheung to
>>>> aggregate the multiple correlations estimates? If so, how can I then
>>>> compare the size of the R2 based on the number of predictors (e.g., is
>>>> the multiple correlations estimates for 3 predictors sig higher than
>>>> for 2)?
>>>>
>>>> Thank you,
>>>>
>>>> Catia
>>>>
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>>>
>>>
>
>
>

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