Sentence examples for binary and multinomial outcomes from inspiring English sources

Binary and multinomial outcomes were described using the number and percentage endorsing.

Loss functions for binary and multinomial data as well as Poisson and time to event (survival) data are also available [ 27].

Data were analysed using binary and multinomial logistic regression.

Odds ratio (OR) and 95% confidence interval (95% CI) were obtained from binary and multinomial logistic regression analysis.

Missing data for the binary measure of self-harm was imputed using logistic models and additional data on demographics employed binary and multinomial logistic models as appropriate.

Analyses will use binary and multinomial logit regression models, as well as generalized linear latent growth models.

Binary and multinomial logistic regression analyses were used to control for confounding factors in the relationship between smoke exposure and CRS status, including age, sex, and race.

The classification capability of the HE4 and CA125 markers, alone and together, was assessed using the binary and multinomial logistic regression models with leave-one-out cross-validation.

Binary and multinomial logistic regression analyses were used to study the relationship between socio-demographic and substance use indicators, and risky sexual behaviours among adolescents.

The magnitude of the associations was measured using odds ratio (OR) and 95% confidence interval (CI) and was obtained by multiple binary and multinomial logistic regression.

The effect of baseline AQoL ≤ 0.0 upon hospital utilisation and place of residence during follow-up was assessed using binary and multinomial logistic regression models respectively.