We were able to estimate a stable model, though, by constraining ORs for particular types / numbers of disorders to be the same in predicting both planned and unplanned attempts unless the interaction of the predictor with plans in the pooled model was significant at the α level of.05 and had an estimated variance inflation factor (a diagnostic test suggesting that a regression coefficient might be affected
by multicollinearity) of less than 10.0.
However, analysis of regression structure coefficients (child report of adherence rs =.67, parent report of adherence rs =.59), which are not suppressed or inflated
by collinearity, demonstrates that beta weights for adherence are low because of
multicollinearity between predictors, not poor relations with the outcome variable.