Sentence examples for regression technical from inspiring English sources

Additional file 1: Fixed effects regression (technical details).

We calculated incidence risk ratios for demographic characteristics by using a negative binomial regression (Technical Appendix).

In the regression analysis, technical efficiency was positively related (in both the scenarios/cases) with an urban location of health centers (except in the case where in the study were included the 5 rural health centers where the dentist work without assistant) and a low time per patient.

The dependent variable of interest for the Tobit regression was technical efficiency score of health facilities which was right-censored using the upper limit of 1.0 (equivalent to 100%%), thus facilities that fall below this limit were deemed inefficient relative to their peers.

Using regression techniques (Technical Appendix), we statistically examined the relationship between the number of cholera cases in each health district and the following list of geographic and environmental variables: area; population; and presence/absence of cities of >100,000 inhabitants, of railway stations, of harbors, of major tracks or roads, and of lakes.

40 In the Tobit regression analysis, the technical inefficiency scores were regressed against a set of environmental characteristics and several institutional factors.

An empirical study based on data from 2006 to 2008 for the US airline industry finds that the regress of productivity is mainly caused by a demand fluctuation in 2007 2008 rather than technical regression in production capabilities.

The first regression models employed technical wind park attributes and perceived simulation realism factors.

Because these unobservable individual effects were cancelled out by within-transformation in FE-regression (for more technical details: [ 7] and Additional file 1), time-constant unobserved heterogeneity is no longer a problem.

Regression analyses showed that technical system knowledge and ecodriving motivation were both important predictors for ecodriving efficiency.

We previously showed that lexpit regression addresses the main technical challenges to additive risk analysis of binary data in cohort studies [ 13].