Sentence examples for using a multinomial model from inspiring English sources

To model the simultaneous exceedance of both chemicals, two types of Logistic Regression (LR) models were developed by (a) treating arsenic and nitrate independently and combining the marginal probabilities of their exceedance, and (b) treating the two exceedances together by using a multinomial model.

We then focused on those women reporting sexual IPV, dividing them into those reporting sexual but not physical IPV and those reporting both, and comparing each group to those reporting no sexual IPV using a multinomial model.

In this network, variables are modeled using a multinomial model with Dirichlet priors, as is described elsewhere[ 14- 16].

The first step was to estimate the outcomes of change in BCVA for dexamethasone that were compatible with those available for ranibizumab using a multinomial model.

An alternative would have been to allow choices between more than 2 potential recipients using a multinomial model, or to have more attributes and levels; but this would have complicated decision making [ 22].

These frequency values were transformed in log2 probability ratio values with the PWM function implemented in the Bioconductor Biostring package, using a multinomial model with a Dirichlet conjugate prior to calculate the estimated probability of base b at position i.

More recent work has used a multinomial model for node degree in the presence of false positives and false negatives, but is not directly applicable to pooled screens where clones are sampled to identify interacting pairs (Scholtens et al., 2008).

From an analytical standpoint, it may have been advantageous to use a multinomial model to deal with the issue of competing risks (i.e. more episodes were excluded due to admittance to a hospital or other inpatient facility than experienced the functional decline).

The data were analyzed using a multinomial logit model, sometimes referred to as a generalized logit model (Allison, 1999; Hosmer & Lemeshow, 2000; McFadden, 1973).

We model the probability that the patient will fall into any of those categories, using a multinomial logit model.

Inferences are made using a multinomial logit model (MNL).