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We use conditional logistic regression to predict the log-odds of collision risk at intersections and mid-blocks as a function of various environmental measures while controlling for volume of child pedestrian activity.
For statistical analysis, we will use conditional logistic regression models and a Cox proportional hazard regression model.
Results We use conditional logistic regression to compare our Adjusted Haplotype Conditional Entropy (H|H) measure of positive selection to existing positive selection measures.
We planned to use conditional logistic regression to carry out a matched analysis but found that this method did not enable us to apply weights.
Because cases of MSD are matched with 1 or more controls, we use conditional logistic regression (CLR) modeling to estimate associations with MSD [ 14].
Because a strict case control match was not maintained, we did not use conditional logistic regression modeling except as a check on the findings from logistic regression models.
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Adjusted odds ratios (ORs) for vaccination were calculated using conditional logistic regression, controlling for underlying conditions.
We then used conditional logistic regression to analyze the data.
Relative risk (RR) was calculated using conditional logistic regression.
We analyzed the association between anti-Hu reactivity and SCLC using conditional logistic regression.
We used conditional logistic regression analyses to compute the adjusted odds ratios.
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