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c Because of missing responses, analyses included only 155 women for education level, 125 women for number of live births, 120 parous women for age at first live birth, and 74 parous women for breastfeeding.
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To estimate the impact of missing responses, additional sensitivity analyses were performed, using multiple imputations with "predictive mean matching method" [ 37].
After excluding 86 individuals with missing responses for covariates (see Statistical analyses section), 76,775 individuals were included in analyses to calculate the propensity score and 54,960 individuals were included in analyses as responders to the follow-up survey.
While 17%% of the response sample was excluded from analyses because of missing responses, few differences existed between the response and analysis samples.
Of these women, six were missing responses pertaining to uterine leiomyomata, and thus our analyses of this outcome included 1,221 women.
We excluded subjects with more than five missing OHIP responses from the analyses; if there were five or fewer missing responses, the missing values received the subject's median response score [ 23].
We used an expectation-maximization algorithm to impute missing responses for the total of 26 items that were included in the analyses.
Three participants had missing responses to the post-injury life satisfaction outcome question and were therefore excluded from subsequent analyses in this paper.
To address issues of unequal probabilities of selection and modification for missing responses, appropriate weight variables (i.e., wtmec2yr, sdmvstra, and sdmvpsu) were used in all statistical analyses.
No imputation was performed for missing responses.
We excluded trials with missing responses or missing confidence ratings.
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