More importantly, though, mean centering does not really affect multicollinearity. Without the interaction terms, in fact, the results with and without mean centering are identical. And if you calculate effects
Multicollinearity was assessed by inspection of the variance inflation factors and tolerance statistics [32]. In addition to basic descriptive statistics, correlation analysis and t-tests to compare means, stepwise hierarchical regression analysis was performed to examine the predictive values of the inde...
The two predictors were scale-centered to reduce multicollinearity and facilitate interpretation of the coefficients on the x–y plane, where the origin of the x-axis and y-axis is located (Edwards, 1994). Then, we created three new variables per OC dimension: the square of the centered ...
Learn about factor analysis - a simple way to condense the data in many variables into a just a few variables.
Clearly, the green line does not fit the data at all. Its slope is nowhere close to being correct, and its fitted values are biased. When it comes to using and interpreting the constant in a regression model, you should almost always include the constant in your regression model even thoug...
What factors must an analyst consider to decide whether the correlation is meaningful enough to investigate further? Why is multicollinearity a problem for inference in regressions? What are some descriptive and non-descriptive methods of data analysis that can ...
For the purposes of this study, the SPSS 22.0 program was used. Descriptive analysis was employed to evaluate the sample’s demographic characteristics and calculate the mean scores of consumers’ perceptions and attitude. To examine consumers’ perceptions of three types of home IoT services, repeat...
The yearly land use data utilized in this study were obtained from the MOD13Q1.006 product, with a spatial resolution of 500 m. These data were processed via Google Earth Engine. The NDVI data were derived from the MOD13A1 product. To calculate the annual mean for each pixel, all the ac...
Logit regression is used to estimate the parameters of the logistic model. Answer and Explanation:1 The least-square method gets greatly affected by the presence of outliers as it recognizes the given data in terms of their squared distances from... ...
The Position Generator also enabled to calculate the mean occupational prestige in respondents’ network. Lin and Dumin state that people’s position on the socioeconomic ladder (as measured by their occupational position) is positively connected with access to social capital [56]. Therefore, having...