Sentence examples similar to a probit model for ordered outcomes from inspiring English sources

Because the dependent variable (having a tocolytic hospitalization) was binary, we estimated a probit model for this outcome.

To this end we used an ordinary least squares model (robust for heteroscedasticity) for the effects of healthcare costs, a probit model to identify the likelihood of job losses, and an ordered probit model to analyze the effects of the amount of informal care received.

MCMCglmm only supports the probit model for an ordinal outcome, so that program was not used for the ordinal case.

The exception is the probit model, developed for ordered categorical phenotypes.

The estimation was conducted using an ordered probit model for the total population first, and then for a subgroup of rural lower income households.

We use an ordered probit model for investigating changes in the probability of finding negative, positive, and insignificant impacts.

We then developed a multinomial ordered probit model for the distribution of titers over three sampling periods to allow the rate of change in the distribution of HI and MN titers to be estimated.

Table 5 presents the results of the estimation of a generalized ordered probit model for panel data.

The statistical models discussed in this paper were organized according to the type of outcomes: i) logistic and probit models for binary outcomes, ii) multinomial logistic and probit models for nominal outcomes, and iii) bivariate probit model for bivariate binary outcomes.

For each age group, we estimate a probit model.

For the binary satisfaction outcome (i.e., reporting of no problems), a probit model was specified and estimated by maximum likelihood.