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The landslide susceptibility index was obtained by logistic regression model.
By logistic regression model analysis, increasing agriculture benefits and new technology popularization were key factors affecting farmer behavior.
cAdjusted for included variables (age, triage level, arrival time, LOS, medical complaint) by logistic regression model, based on 42,327 observations (40,234 visits of patients who did not return and 2,093 unscheduled return visits) due to missing values on triage level (n = 1,584).
Odds ratios (OR) and their 95% confidence intervals (CI) were computed by logistic regression model analysis to clarify the impact of several potentially independent prognostic factors.
Furthermore, the relationship of radiation dose and chemotherapy with xerostomia was tested by logistic regression model.
RORs were estimated by logistic regression model separately for each meta-analysis.
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The Student t-test and the chi-square test were applied; additionally, the magnitude of the association between independents variables and HDP was estimated by logistic regression models.
One possibility would be to estimate the response propensities of respondents by logistic regression models and compute the weight adjustment factors based on these models (e.g., Lepidus Carlson and Williams 2001; Watson 2012).
Odds ratios were assessed by logistic regression models adjusted for age, BMI and gender.
Among the seven associations supported by logistic regression models, A*36 and DRB1*0102 were among the most unfavorable, while Cw*18 and B*57 were among the most favorable.
The statistical significance of associations between the covariables and the latter were examined by logistic regression models controlling for age and BMI.
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