What is Multicollinearity in Multiple
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What is Multicollinearity?
Multicollinearity occurs when variables are so highly correlated with each other that it is
difficult to come up with reliable estimates of their individual regression
coefficients. When two variables are highly correlated, they are basically
measuring the same phenomenon or construct. In other words, when two variables
are highly correlated, they both convey essentially the same information.
way to asses the possibility of multicollinearity among your study variables is
to perform correlations. If a correlation coefficient matrix demonstrates
correlations of .75 or higher among your variables, there may be
multicollinearity. Other statisticians suggest that correlations of .90 or
greater may indicate multicollinearity. If this is unclear, request a free
research consultation today to receive help with evaluating your multiple
regression for multicollinearity.
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Let Us Help You Identify & Eliminate Multicollinearity
Since multicollinearity can adversely affect the
results of your multiple regression, it is important that your analyses are
properly evaluated to determine the presence of multicollinearity. We can assess for the
presence of multicollinearity in your study and provide methods for correcting
or reducing its influence. In addition, if you are unsure what statistical test might be
the most appropriate and powerful for your study, let us review your research
question to help you choose the best statistical test for your study or research
project. Request Statistics Help Today!