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*Adjusted for matching variables of age, sex, and calendar year.
27 The imputation model included all covariates from the main outcome model, together with matching variables of age and sex, and extra comorbidities as additional markers of alcohol or smoking related diseases.
This model includes the matching variables of age, place of living and the acknowledged predictors in the aetiology of breast cancer from high-income countries.
By matching on year of birth, we found a small but significant difference in age (69.9 vs. 69.8 years; P = 0.001), but the matching variables of sex (57.7% men) and diabetes duration (5.3 years of observation) did not differ.
We then performed logistic regression analysis, conditioned on the matching variables of gender, age, and study area, and presented the odds ratios (ORs) that represent the risk associated with a positive family history of stomach cancer.
We did not use conditional models because of the uneven numbers of cases and controls, but instead forced the matching variables of child age and sex into all models, as strategy suggested by Rothman and Greenland [ 18, 19].
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The reason for not matching on such variables was twofold: First, after matching, the effect of the matched variables on the outcome cannot be assessed; second, matching can introduce bias in case-control designs.
Our algorithm is no more domain-independent because of our weighting procedure of matching variables, and because of our names frequency based weighting.
For each case, control subjects were selected from a randomized subset of combination of matching variables without replacements.
Cases and controls had similar distributions of matching variables, age, gender, race and county of residence as well as education, body mass and alcohol consumption.
This approach eliminates the influence of matching variables, such as sex, age, county of residence and calendar year at CD diagnosis.
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