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Exact(4)
Two samples had missing gender and age data.
SD, standard deviation * p < 0.05 ** Of the 10269 total number of samples received, 85 and 56 were missing gender and ethnicity data, respectively.
We dropped 635 encounters in 20 individual patients because of missing gender and 3 encounters in 3 individual patients because of missing age.
There were 1,087 (4.5%) individuals missing information on injecting duration, 504 (2.1%) missing HCV test status, 465 (1.9%) missing age, 140 (0.6%) missing gender, and 2 (0.008%) missing region of recruitment.
Similar(56)
The missing gender bias and the higher frequency among smokers repeated in our sample support the validity of our data.
IQR=Interquartile range †2 participants were missing gender data; *Comparison is between males and females; **Data missing for Lainya 2009, Ronyi 2009.
Of those having mentors, four were males, two females, and two records were missing gender data.
The results of the weighted, censored, negative binomial regression analysis using participant's age, gender, household size, day of the week, period (holiday or not) and country as explanatory variables are summarized in Table 2. * Missing age was equally distributed over the other variables ** Missing gender was associated with weekday, regular period and household size 1-4.
Gender distribution of the 12,395 participating pupils was 6,799 females and 5,529 males (67 with missing gender data); the mean age was 14.91±0.90 (83 with missing age data).
In the unrelated group (104 unexposed boys, 2 exposed boys, 106 unexposed girls, 7 exposed girls; 2 unexposed with missing gender), there is no significant association between smoking in pregnancy and ADHD in either boys (β = −.114, p =.246) or girls (β =.010, p =.914).
The overall sample consisted of 501 female (55 %) and 392 male (44%%) participants, with 13 participants missing gender data (1 %).
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