Sentence examples for multilevel regression and from inspiring English sources
By using the PISA 2003 data set of 41 countries, we apply multilevel regression and confounder analyses to investigate these effects for each country.
As said earlier, the current statistical packages do not allow for the combination of cross-classified multilevel regression and different plausible valuesi.
We were forced to use this average score, because the current statistical packages do not allow for the combination of cross-classified multilevel regression and different plausible values (see section 'analyses and results', paragraph 'methods'methods
Our model is based on a frequently used survey technique called multilevel regression and post-stratification.
Skovron is an expert in a modeling technique designed to estimate district-level opinion called multilevel regression and poststratification (MRP).
How they estimated those Electoral College tallies - The analysts at Morning Consult used data they had collected from national surveys since January and a statistical technique called multilevel regression and poststratification (MRP) to estimate which candidate would win each state in a hypothetical election.
* p < 0.05; ** p < 0.01 Overall, smaller and larger practices (multilevel regression analysis and logistic regression analysis).
The database of Netherlands Information Network of General Practice was used to determine the prescribing behaviour in Dutch FPs by conducting multilevel regression models and adjusting for patient and practice characteristics.
We carried out a cross-sectional analysis of data on more than 19,000 white adults aged 45 and older who participated in three representative surveys of the English population in 1994, 1998 and 2003, examining the relationship between self-reported doctor-diagnosed cardiovascular disease and exposure to outdoor air pollutants using multilevel regression techniques and meta-analysis.
By way of multilevel regression, primary and secondary outcomes will be set in relation to structures and processes.
Additionally, we used a linear multilevel regression model and a negative binominal regression model.
