Sentence examples for intervention by time from inspiring English sources

MANOVA results revealed that the main effect of testing time, the main effect of intervention, which favored the semantic search engine group, and the interaction effect of intervention by time led to significant differences between students' achievement scores.

As part of the sensitivity analysis we will also examine intervention by time period interaction.

Intervention by time interaction was estimated to test for global group differences and for global change over time between groups.

This may indicate a reduced effect of the intervention by time and a need to reinforce the education.

To examine intervention by time interaction effects, mixed effects regression will be used due to the multi-level and hierarchical nature of the data.

To account for cluster randomisation, sample size calculations were based on recent methods developed by Heo & Leon [ 46] to detect intervention by time interactions in longitudinal cluster RCTs.

For A1c control, medication intensification increased in both groups (intervention, pre 26.4% vs post 32.6%, p=0.022; control, pre 24.8% vs post 31.1%, p=0.033) (intervention, adjusted OR (AOR) 1.37; 95% CI 1.06 to 1.76; control, AOR 1.41 (95% CI 1.06 to 1.89)); however, we observed no incremental benefit solely due to the intervention (group-by-time interaction, p=0.948).

Although the intervention had no significant advantage compared to the control intervention, group by time analyses found a significant improvement in coping (F 1,70) = 4.01, p < 0.05).

These models will allow for 1) comparing patterns of change over time by testing the intervention group by time interaction and 2) estimating and testing differences in outcome measures between groups at time points of interest via linear contrasts.

Eight weeks of whole body vibration (30 Hz, 1.5 mm) in the unloaded half-squat position improved running economy by 7.7%% compared with the 1.9 % gain after the passive control intervention (group by time interaction, p < 0.05; effect size = 0.93).

Mixed model account for covariance between repeated measures on patients and allow for: 1) comparing patterns of change over time by testing the intervention group by time interaction; and 2) estimating and testing differences between groups at time points of interest via linear contrasts.