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The Age of Missing Information contrasted the knowledge gleaned from cable TV over 24 hours with a day spent on a mountain.
Bill McKibben called ours "The Age of Missing Information" because the media deprive us of the contact with nature that was once taken for granted.
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It was an age of missed opportunities and weak but brutal rulers, sandwiched between two periods of foreign domination.
Our final models contained all of the previously listed potential confounders and in addition controlled for body anthropometrics as potential mediators (baseline BMI [calculated from measured weight and height], height and measured waist circumference, and self-report of BMI at age 50 years; because of missing data, age 50 years BMI was imputed from age, race, and baseline BMI in 128 women).
Because missing data can have deleterious effects on analyses that depend on branch length [ 102], we tested the effect on age estimates of missing sequences in our data set.
The overall rate of missing gestational age was low, however (0.9percentt among white live births and 0.8percentt among black live births).
We looked at the association between education of mother and maternal age and proportion of missing data on paternal age.
Exclusion criteria were patients younger than 18 years of age, missing CRP data at discharge or loss to follow-up due to transfer to another hospital.
We examined whether the independent variables, period (≤1996 or > 1996), sex and age, were predictors of missing medical records, and we found that period was a strong predictor, whereas age was a weak predictor, whereas sex was not.
These results were robust to changes in age and imputation of missing data.
Spearman rank correlation coefficients were calculated to evaluate the association of age and number of missing teeth, totally and anteriorly, with the OIDP score.
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