Dear Statalisters,
I have a data set of four studies that I would like to meta-analyse using a random effects model. In the papers, the data is presented as incidence, as per study 2 the incidence is 66.8 per 100,000 person years compared to the general population of 5.7 per 100,000 person years. They do not supply total person years from their study. The data from the studies is in Table 1 below:
Table 1
I get the effect sizes (ES) and their pooled ES by using :
metan logirr selogirr,random eform
but the problem is, that I need to get the correct weight of the random effects model from the sample size of cases (variable name samplesizeofcases), and not the computed ES-- personyear1 event1 personyear0 event0. I only have the data in Table 1 to work with.
The weight assigned (Table 1 WT variable) for study 2 with the biggest sample size (n=14506) was only 9.1%, as opposed to study 4 with 72% of the weight but only 9381 cases total. This is wrong.
Any suggestions on how I should proceed?
Many thanks in advance, Carole
Reference: Bagos PG, Nikolopoulos GK. Mixed-effects Poisson regression models for meta-analysis of follow-up studies with constant or varying durations. 2009, The International Journal of Biostatistics, 5(1), Article 21 [PDF] http://www.compgen.org/tools/poisson-meta-analysis
I have a data set of four studies that I would like to meta-analyse using a random effects model. In the papers, the data is presented as incidence, as per study 2 the incidence is 66.8 per 100,000 person years compared to the general population of 5.7 per 100,000 person years. They do not supply total person years from their study. The data from the studies is in Table 1 below:
Table 1
| study id | personyear1 | events1 | personyear0 | events0 | patientswithtb | samplesizeofcases | followuptimeyears | selogirr | logirr | _LCI | _UCI | _WT |
| 1 | 9672 | 13 | 100000 | 11.9 | 13 | 2806 | 6 | 0.401194 | 2.424346 | 5.144972 | 24.79574 | 10.78166 |
| 2 | 100000 | 66.8 | 100000 | 5.7 | 37 | 14506 | 6 | 0.436358 | 2.461237 | 4.982791 | 27.56326 | 9.113976 |
| 3 | 21620 | 105 | 100000 | 69.8 | 105 | 4131 | 12 | 0.154436 | 1.939878 | 5.140697 | 9.41747 | 72.76086 |
| 4 | 9381 | 7 | 100000 | 10.7 | 7 | 9381 | 2 | 0.486123 | 1.94215 | 2.689533 | 18.08229 | 7.343501 |
| gen selogirr=sqrt( 1/events1 + 1/events0) |
| gen logirr=log( (events1/ personmonth1)/( events0/ personmonth0)) |
metan logirr selogirr,random eform
but the problem is, that I need to get the correct weight of the random effects model from the sample size of cases (variable name samplesizeofcases), and not the computed ES-- personyear1 event1 personyear0 event0. I only have the data in Table 1 to work with.
The weight assigned (Table 1 WT variable) for study 2 with the biggest sample size (n=14506) was only 9.1%, as opposed to study 4 with 72% of the weight but only 9381 cases total. This is wrong.
Any suggestions on how I should proceed?
Many thanks in advance, Carole
Reference: Bagos PG, Nikolopoulos GK. Mixed-effects Poisson regression models for meta-analysis of follow-up studies with constant or varying durations. 2009, The International Journal of Biostatistics, 5(1), Article 21 [PDF] http://www.compgen.org/tools/poisson-meta-analysis
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