エビデンス総体におけるmissing dataに関連したGRADEのRoB評価です。
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●When assessing risk of bias associated with participant outcome data across an entire body of evidence, we propose using a complete case analysis for the primary meta-analysis.
●When the results of the primary meta-analysis suggest a statistically significant treatment effect, conduct sensitivity meta-analyses using plausible assumptions to impute events in participants with missing outcome data in each study, and then pool across studies.
●If the results of the primary meta-analysis are robust to the most extreme plausible assumptions, one does not rate down certainty in the evidence for risk of bias due to missing participant outcome data.
●If the results are not robust to plausible assumptions, one would rate down certainty in the evidence for risk of bias.
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“missing dataの対処については、本ブログですでに解説しています。
*欠損値（missing data）に関するimputation strategy
*小児の出っ歯は、7～11歳ごろに矯正治療を開始すべきか、早期青年期（11～16歳）に開始すべきか ー[2b-1]
*小児の出っ歯は、7～11歳ごろに矯正治療を開始すべきか、早期思春期（11～16歳）に開始すべきか ー[2c]
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