Sentence examples for multivariate probit regression from inspiring English sources

Most approaches to maximum likelihood estimation in multivariate probit regression rely on Monte Carlo EM algorithms to avoid computationally intensive evaluations of multivariate normal orthant probabilities.

The associations between system components and intermediate outcomes of diabetes care were assessed using multivariate probit regression [ 14].

There are analytic methods to adjust for endogeneity bias in cross-sectional data (e.g., propensity score matching, bivariate probit regression, multivariate probit regression and instrumental variable regression) [ 68].

A total of 112 FLT3-ITD negative AML patients were sampled between 2010 and 2013, and the occurrence of PRL-3 hyperexpression in FLT3-ITD negative AML was evaluated by multivariate probit regression analysis.

The third step was the use of multivariate probit (MVP) regression model.

This supports the use of a Multivariate Probit (MVP) regression model in the analysis of these data.

To analyse the interdependent decisions of adaptation and coping strategies by farmers, Multivariate probit (MVP) regression was applied (Greene 2012).

Multivariate probit (MVP) regression model was used to identify these key factors that affect farmers' coping and adaptation strategies to the declining trends of rainfall and crop productivity.

Further, we used multivariate ordered probit regression estimates to examine the levels and factors associated with Catastrophic Maternity Expenditure (CME) at different thresholds based on the share of maternity care expenditure in total annual income.

For the multivariate analysis, ordinal probit regression analysis (with CLM in the "ordinal" package) was used in the " R for statistical computing" environment, version 2.16 [ 18– 20].

Table 4 illustrates regression outputs of the multivariate probit model.