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We arbitrarily assume six time-points at which the predictor, outcome and mediator are measured.
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This article outlines a general framework for evaluation of these types of requirements, using a predictor-outcome N-way matrix.
Tables 7 and 8 in Appendix summarizes the evidence using a form of predictor-outcome matrix (Miles and Huberman 1994: 213 et seq).
The structural equation model combining the hypothesized item-factor relationships from the factor analyses and predictor-outcome relationships derived from the previous univariate regressions fit the data with an RMSEA of 0.047, which is well below the criterion of good fit of 0.06 proposed by Hu and Bentler ([1995]).
Structural equation modeling allows the analyst to assess and compare various models relating predictors, outcomes, mediators, and moderators (Kline 2005).
Fortunately, numerous papers contain baseline population characteristics from which univariable predictor-outcome associations can be derived.
Finally, our simulation study only evaluated the performance of estimated multivariable predictor-outcome associations.
Diagnostic and prognostic literature is overwhelmed with studies reporting univariable predictor-outcome associations.
Additional research is needed to evaluate the extent to which improved predictor-outcome associations result in an improved model performance.
Two authors provided estimated predictor-outcome associations that were not described in the original reports [ 39, 40].
We assessed potential effect modification by including an interaction term between barriers score and the potential effect modifier in the primary predictor-outcome models.
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