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The importance of particular combinations of traits in predicting ASD status was investigated using logistic regression (see Table 4).
The relationship between the number of antigens recognized at high titre by each individual and group (UMA, ACHP and ACLP) was also investigated using logistic regression.
The most likely genetic model for rs2228671 on serum LDL-C and for rs2228671 on CAD was investigated using logistic regression models and the Minelli approach[21] (details see supplement)16, 22.
Differential item functioning was investigated using logistic regression.
Possible confounders were investigated using logistic regressions models.
Risk factors for H. pylori infection were investigated using logistic regression.
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Parameters associated with initial hyperlactatemia and lactate clearance were investigated using multivariate logistic regression analysis.
Associations were investigated using univariate logistic regression when the dependent variable was dichotomous and Pearson correlation for continuous variables.
Additionally, associations between the changes in cytokines and 90-day mortality were investigated using multiple logistic regression analysis.
The effects of physical, socioeconomic, and neighborhood factors on urban expansion and their temporal dynamics were investigated using binary logistic regression.
In this work factors influencing the development of red discoloration in chicory heads stored in controlled atmosphere conditions were investigated using multiple logistic regression analysis.
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