Therefore, we also calculated a second set of weights by multiply imputing missing predictors of missingness.
The results obtained using this second set of weights were very similar to those (reported below) obtained using missing indicators.
After finding the first set of such weights, CCA iterates min{ t, f} times to find more weight vectors, such that the resulting canonical variates are not correlated with any of the previous canonical variates.
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We calculated body mass index by using the first set of height and weight data available for each patient.
The first set of models (A: birth weight) showed that although there was some evidence of a positive relationship between birth weight and CVD, this was not statistically significant either before or after adjustment for sex, paternal occupation at birth, gestational age at birth and exposure to the 1940 45 occupation (see Table 1).
Finally, the power calculations indicated that the analyses in the first set of models (A: birth weight) are likely to have been underpowered.
The first set of models (A: birth weight) included sex, gestational age at birth and paternal occupation at birth (as potential confounders) and exposure to the 1940 45 occupation (as a competing exposure).
In a first set of experiments, the Score Function's weighting parameters θ 1,θ 2, and θ 3 have a fixed value of 0.3, 0.3, and 0.4, respectively.
