Sentence examples for simultaneous regression from inspiring English sources

Figure 1 shows the results from the simultaneous regression models.

Simultaneous regression techniques lead to more efficient estimators.

A simultaneous regression design was used to assess the unique variance associated with each variable.

To examine these relations in more detail we submitted all three variables to a simultaneous regression predicting the estimates of GPA.

Neutron reflectivity was measured for both surface concentrations using three different sets of neutron scattering length density contrast conditions, and models for the distribution of PEG and lysozyme content in the layers were obtained by simultaneous regression of all contrast condition data sets.

To test this, we ran a simultaneous regression model for each measure, entering both trial number 1-1500) and corresponding block trial number (0-49).

This paper uses simultaneous regressions (i.e. path analysis in SAS's PROC CALIS) to estimate the relationship between field saturation, field transferability, field-of-study mismatch, overqualification and wages.

The order of entry into models is irrelevant in simultaneous regressions (unlike in hierarchical regression).

It is important to emphasize that the order of entry is not important when using simultaneous regressions.

Specifically, we choose simultaneous quantile regression over quantile regression because it enabled us to test for the similarity of effect of our independent variables at different points in the dataset.

This is a unique facet of simultaneous quantile regression relative to quantile regression [ 26, 27].