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As cases and controls will be frequency-matched, unconditional logistic regression with matching variables as covariates will be employed.
We adjusted for potential confounders and matching variables.
An initial model was adjusted only for matching variables.
*Adjusted for matching variables of age, sex, and calendar year.
An initial 'model 1' adjusted only for matching variables.
All logistic models were adjusted for matching variables.
Table 1 shows the distribution of the 68 lung cancer cases and controls by matching variables.
Table 1 shows the distribution of NHL cases and control subjects by matching variables.
Weighting scores were assigned to matching variables, including full name, sex, date of birth, and address.
No statistical analysis was performed on age and sex, which were matching variables between groups.
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All models were adjusted for the frequency-matching variables.
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