There are probably variables in the model with data that is similar to other variables, producing multicollinearity. CSIndex values are monotonous or missing. ranking - sorting numerical or ordinal variables in ascending order multicollinearity - when one predictor variable in multiple regression model can be linearly predicted from the others problem of multicollinearity - the coefficient estimates of the multiple regression may change erratically in response to small changes in the model or the data some causes of multicollienarity: inclusion of a variable which is computed from other variables in the data set; the repetition of the same kind of variable. scaling - normalizing data to a common range See also, The Panel procedure: Unbalanced data
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