Sentence examples for multivariable modelling was from inspiring English sources

Multivariable modelling was used to determine the effect of treatment on 6 week in-calf rate, adjusting for design factors (study year and region).

Multivariable modelling was achieved using multiple linear regression.

Multivariable modelling was pursued in stages (table 3).

Multivariable modelling was used to identify factors associated with being screened.

Controlling of these types of confounders with multivariable modelling was not possible in our study due to very small number of MRSP positive dogs.

The multivariable modelling was, conceptually, a straightforward analysis of social distance as a function of (a) the disease characteristic and (b) the co-characteristic.

Parameter estimates for multivariable modelling are often not stable when presence of a variable occurs infrequently.

Statistical significance in the multivariable models was declared at P < 0.05.

The multivariable model was built using all variables significantly associated with ICU mortality in univariate analysis (p < 0.05).

The estimated coefficient for HD in the multivariable model was −20.4 (95% confidence interval: −26.3 to −14.4) (Table 2).

A single multivariable model was produced.