Interpreting Multiple Linear Regression: A Guidebook of Variable Importance

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Importance-Performance Analysis based SWOT analysis (2016, methodology): “The regression coefficients obtained from the MLR model can be referred to as implicit importance since the regression coefficient generally indicates how much a one unit increase in the independent variable results in an increase or decrease in the dependent variable with all other variables held c”
Variance Inflation Factor: As a Condition for the Inclusion of Suppressor Variable(s) in Regression Analysis (2015, background): “The use of suppressor variables in multiple regressions is more common than currently recognized [13] [14].”
Understanding the Results of Multiple Linear Regression (2013, background): “As noted by Nathans, Oswald, and Nimon (2012), each metric serves a different purpose and has certain features that support interpreting specific aspects of a multiple linear regression (MLR) model (see Table 1).”
A comparative study of machine learning classifiers for modeling travel mode choice (2017, background): “225 Numerous approaches for quantifying variable importance for different models have been proposed (e.g. 226 Olden et al., 2004; Hagenauer and Helbich, 2012; Nathans et al., 2012).”