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One possible reason for this counterintuitive effect could be the high percentage of missing values associated with this variable could have affected the results.
Missing Values: associated tumor (138); DM and/or High lipid (128); Inflammatory disease (158); Smoking (131); Inmobility (166); Surgery Intervention (126); Nephrotic Syndrome (164); Myeloproliferative Syndrome (159); Trauma (159).
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Importantly, the data available on ethnicity were incomplete and the proportion of missing values was associated with fitness to practise outcomes.
Non-response to the third questionnaire and exclusion in this study due to missing values was associated with low education, being male, and ages 20 39 and ≥70 years.
Missing values were not associated with any particular day in the week.
The variable FARMA with mean-imputed values replacing missing values was significantly associated with the outcome, and its inclusion in the model resulted in slight modification of the effect estimates for CATDENSITY, HERSIZE, AVETEMP and OPENCLOSED (see Table 3).
Furthermore, associations between FA exposure and wLRI were confirmed in sensitivity analysis: After multiple imputation for missing values, adjusted ORs associated with an interquartile increase in FA levels were 1.16 (95% Cr: 1.04, 1.29) and 1.19 (95% Cr: 1.06, 1.32) for LRI and wLRI, respectively.
Missing values on silhouettes were associated with a significantly increased diabetes risk, and they were more frequent both among overweight or obese women (P < 0.001 for birth weight and each body silhouette, except at age 20 25 years, P = 0.012) and among older women (P < 0.001 for birth weight and each body silhouette) independently.
Coverage plots [ 28] were constructed to examine whether exon length was associated with missing values.
These missing values would also render other associated data unusable, resulting in significant data wastage [ 8].
Factors associated with missing values for this variable are given in the results section.
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