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We also aimed to evaluate the potential differences in summary estimates between studies defining IRSA as ≥2 and ≥3 spontaneous abortions.
We compared the rank orders of the estimates between studies.
Furthermore, differences in mode and timing of data collection could explain variation in estimates between studies.
I statistics were used to assess heterogeneity of the RR estimates between studies at significantly associated loci.
We assessed heterogeneity of effect estimates between studies using the I statistic (Huedo-Medina et al. 2006).
Similar results were observed in these subsequent analyses, with no statistically significant heterogeneity in risk estimates between studies.
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A random-effects model was used; the overall estimate was calculated by using as weights 1/ vi + τ), where vi is the variance of the estimated effect from the ith study and τ is the estimated between-study variance [ 20].
However, since the number of studies in this analysis is small, the random effects model cannot estimate between-study variance with much precision (Borenstein et al. 2009).
Moreover, breaking down populations to sub-studies may sometimes lead to loss of estimated between-study heterogeneity, if the sub-studies are small and their confidence intervals of effects are very large.
The restricted maximum likelihood method was used to estimate between-study variance.
Imputation quality was high for all four studies contributing this SNP (>0.90, table 2) and the estimated between-study heterogeneity was acceptable (I=0%; p(Q)=0.67).
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