Sentences with phrase «step hierarchical regression»

Three analyses were conducted with the cross-sectional data using teachers» WSS ratings of student achievement and students» WJ - R standard scores: a) correlations comparing the students» standard scores on the various subtests of the WJ - R and the WSS checklist and summary report ratings of student achievement within the corresponding WSS domains, b) four - step hierarchical regressions examining the different factors that accounted for the variance in students» spring WJ - R scores, and c) Receiver - Operating - Characteristic (ROC) curves, which make possible a determination of whether a random pair of average and below - average scores on the WJ - R would be ranked correctly in terms of performance on the WSS.

Not exact matches

The hierarchical regression analysis showed a significant association between greater resilience and lower psychological distress in step 2.

In Step 3, we conducted hierarchical multiple regressions on each of the adjustment variables.

As seen in Step 2 of the hierarchical linear regression predicting crying proneness from destructive overdependence, family and friend support, and their interactions (Table 2), being female, in a relationship, and highly stressed predicted a greater tendency to cry.

Hierarchical Multiple Regressions Predicting 4 - Month Parenting Stress (β's Denoted for Each Step in Model)

Hierarchical linear regressions were conducted in which each social relationship variable at Wave 2 (parent connectedness and supportive friendships) was regressed on its Wave 1 levels, age, gender, race, and Wave 1 sexual risk in the first step.

In the hierarchical regression for predicting T2 Conduct Problems, for example, T1 Conduct Problems was entered together with T1 Direct Aggression as independent variables at step 2, and the PANIBI measures of Direct Aggression was found to contribute to the prediction of T2 Conduct Problems even when T1 Conduct Problems was controlled for (see Table 8); this result can only be due to the non-overlapping parts of these measures.

A three - step, hierarchical regression analysis was performed to predict change in generalized anxiety from cognitive vulnerabilities, sub-dimensions of psychological well - being, and their interaction (as well as T1 generalized anxiety).

Hierarchical Multiple Regression Predicting 4 - Month Maternal Ratings of Infant Distress to Limitations (β's Denoted for Each Step in Model)

As can be seen in Table II, these effects were maintained in the final step of the hierarchical regression, which included interaction terms.