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Because of the categorical nature of the GH outcome variable, we performed multivariable analysis by using ordinal logistic regression.
The association between MD, adult weight gain and fat distribution was evaluated by using ordinal logistic models with random center-specific intercepts [ 27].
The ordinal nature of the dependent variable was taken into account, by using ordinal logistic regression rather than traditional logistic models, which entail a loss of valuable information by combining different density categories.
In addition, the ordinal nature of the dependent variable was taken into account, by using ordinal logistic regression rather than traditional logistic regression models, which entail a loss of valuable information by combining different MD categories.
MD was included as an ordinal response variable, and its association with all the variables of interest was evaluated by using ordinal logistic models with random screening centre-specific intercepts [ 14].
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The association between knowledge of symptoms and each sociodemographic variable was firstly examined using the Wilcoxon rank-sum test (for comparison of two groups) and Kruskal Wallis test (for comparison of more than two groups), followed by a multivariate analysis using ordinal logistic regression.
We imputed normally distributed variables (including primary outcome data) using multiple regression by ordinary least squares, ordered categorical variables using ordinal logistic regression, and other non-normal variables using predictive mean matching.
Normally distributed parameters (including primary outcome data) were imputed using multiple regression by ordinary least squares; ordered categorical variables were imputed using ordinal logistic regression and other non-normal variables imputed using predictive mean matching.
Responses to individual items of the survey of safety culture will be compared between groups using ordinal logistic regression analysis, clustering results by the site from which the data was collected.
We derived a new method for estimating treatment thresholds using ordinal logistic regression and tested it by asking ophthalmologists to review cases of ocular hypertension before expressing how likely they would be to recommend treatment.
Data were analyzed using ordinal logistic regression.
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