Does it matter how many we include? A random data simulation study examining how number of explanatory variables affect model quality in linear regression models describing quantitative data.
This study examined how the number of explanatory variables included in a linear regression model affects model quality. The maximum number of variables was set to 20 and only models describing quantitative data were studied. The effect on model quality was studied through comparisons of models with different numbers of explanatory variables. The models – and the data sets the models were derived