To create an estimation model based on the multiple regression analysis, an initial sample set is structured of learning samples whose actual measurement of the objective variable is known. The initial sample set is multiple-regression-analyzed to obtain an initial multiple regression equation. A ...
We could now transfer the "swimming" and "running" dummy variables into the multiple regression equation because we also have the "running" dummy variable.It allows multiple comparisons to be made:The coefficient of a dummy variable represents the difference between the category that dummy variable...
To conduct the manipulation checks a multilevel regression analysis was conducted with the R package Lavaan 0.6.12 [74]. Since we are interested in the between-subjects results, the within-subject level was saturated by covarying all measured variables [74]. These are not reported. At the ...
In essence, we conduct a regression analysis that correlates the actual population sizes of various areas within the United States (such as states, divisions, or regions) with the number of American Twitter users from different age and gender groups in those specific locations. This analysis helps...
So as parents and as children the only expectation we should have is emancipation of practice of religion and having faith that everything has its own purpose and only we change and break the pattern of dysfunctionality not through violence or regression but through peacemaking process and affectio...
Structural equation model was used to confirm the goodness of fit and evaluation of main hypothesis and to assess other hypotheses regression was used. The results indicate that educational services, processes, people, promotion have positive effect on educational services brand ...
These samples must be large enough to be statistically significant for the building and testing of the ordinal logistic regression model. 4 MULTICOLLINEARITY In general, multicollinearity occurs when two or more predictor variables (also known as independent variables or covariates) in a regression ...
Linear regression using TIME as the independent factor was performed on the accumulations of AUT uniqueness, AUT fluency, and idea convergence in each of the three conditions. The principle results are as follows: (1) TIME significantly positively predicted the accumulation of AUT uniqueness in the...
(i) the linear regression estimator with fixed and random effects, using a one-lag period in the independent and control variables, and (ii) the two-stage dynamic estimator proposed by Arellano and Bond (1991), based on the generalised method of moments, and implemented in Stata by Roodman...
We implement the wrapped axis in the representativeness model when calculating the multivariate Gaussian components of the representativeness equationR(x,h) (Eq.4of the main text). Specifically, the probability density of the Gaussian component along a single wrapped axis can be computed as: ...