[R-meta] proportional meta-analysis
tbedair.ahmed at gmail.com
Wed Feb 7 19:49:44 CET 2018
> On Feb 7, 2018, at 6:07 PM, Michael Dewey <lists at dewey.myzen.co.uk> wrote:
> Dear Ahmed
> Please keep all replies on the list as others may have better ideas than me. Perhaps best if you re-send?
> On 05/02/2018 09:53, Ahmed Tarek wrote:
>> Dear Michael ,
>> Thank you for your reply. Some studies did in fact report retention at 2,3, and 5 years ( or 2 and 3 only) , but these were only a few studies that I included once in the 2 year forest plot and once in the 3 year plot and so forth. The majority were independent studies ( and each study used only one material).
>> I should designate one material as a moderator? and compare it to the rest? and how would I do that? so I can say material GI was significantly worse than material Auto for example?
>> As you can see the material “auto” reported more heterogeneity when compared to material “Blight” ( I had to name it that way so it would show up second), even though auto seemed more homogeneous.
>> Should 95% heterogeneity be a concern? I divided them according to material and follow up time in order to decrease heterogeneity.
>> I really appreciate the help
>> Ahmed Bedir
>>> On Feb 5, 2018, at 10:33 AM, Michael Dewey <lists at dewey.myzen.co.uk <mailto:lists at dewey.myzen.co.uk>> wrote:
>>> Dear Ahmed
>>> Comments in line below
>>> On 04/02/2018 17:55, Ahmed Tarek wrote:
>>>> Dear all,
>>>> I am quite the beginner when it comes to R. I have recently started to do a meta-analysis investigating the retention of different dental fissure sealers. The dataset included: study name, length of study (2,3,5, years), total number of teeth initially sealed, number of teeth sealed at the end of study, material used for this study.
>>> Are these independent studies at each lenght of follow-up or do studies give informaiton at more than one follow-up duration?
>>>> I divided data according to follow up, and made a proportional meta analysis forest plot comparing the different materials after 2 years (another plot for 3 yr, and another for 5). I made the proportional meta analysis based on the Random effects model using the package “meta”.
>>> I think you are using metafor, not meta?
>>>> 1. If material X was worse than material Y, can I show that the difference was statistically significant? (considering I was comparing 5 different materials at the same time)
>>> Yes, you need to use material type as a moderator assuming each study only used one material. If studies used more than one material you need something more complex.
>>>> 2. I noticed the heterogeneity results (I^2) to be higher for a certain material even though on the forest plot, the results did not seem that heterogeneous when compared to other groups that reported lower heterogeneity. Is that ok? also the study weights did not necessarily represent study sample size, would that be because I used the DL method?
>>> In random effects models the weights become more similar as the heterogeneity increases.
>>>> ######CALCULATE OVERALL SUMMARY PROPORTION#######
>>>> ies.logit=escalc(xi=cases, ni=total, measure="PLO", data=dat)
>>>> pes.logit=rma(yi,vi,data = ies.logit, method = "DL", weighted = TRUE)
>>>> pes=predict(pes.logit, transf = transf.ilogit, digits = 5)
>>>> print(pes,digits=5); print(pes.logit,digits=4);confint(pes.logit,digits = 2)
>>>> #####CALCULATE SUBGROUP ACCORDING TO MATERIAL#######
>>>> pes.logit.Auto=rma(yi,vi,data=ies.logit,subset=material=="Auto",method = "DL")
>>>> pes.logit.Light=rma(yi,vi,data=ies.logit,subset=material=="BLight",method = "DL")
>>>> pes.logit.F=rma(yi,vi,data=ies.logit,subset=material=="F",method = "DL")
>>>> pes.logit.GI=rma(yi,vi,data=ies.logit,subset=material=="GI",method = "DL")
>>>> pes.Auto=predict(pes.logit.Auto, transf=transf.ilogit, digits = 5)
>>>> pes.Light=predict(pes.logit.Light, transf=transf.ilogit, digits = 5)
>>>> pes.F=predict(pes.logit.F, transf=transf.ilogit, digits = 5)
>>>> pes.GI=predict(pes.logit.GI, transf=transf.ilogit, digits = 5)
>>>> 3. For the 2 year studies, almost 100 studies were included, making the forest plot look a bit crammed, should I use another package, that could make it look better?
>>>> 4. I also could not arrange the materials the way I wanted in the forest plot, they kept being arranged alphabetically, even though I used the command “sort=FALSE”
>>> Did you mean to use the ordered parameter, not sorted?
>>>> I really appreciate the help.
>>>> Ahmed Bedir
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