Sentence examples for model analyses indicated from inspiring English sources

Results of hierarchical linear model analyses indicated that the regulation of both positive and negative affect from the prior day to the current day predicted significantly greater decreases in pain that day, resulting in up to a 28% reduction in pain intensity.

At 0600 UTC on 26 September, European Centre for Medium-Range Weather Forecasts (ECMWF) model analyses indicated the existence of two low-pressure areas along the shoreline of Italy, one on the west coast, sweeping eastward across the Tyrrhenian Sea, while the other, slightly more intense, low was located over the Ionian Sea.

Longitudinal mixed effects model analyses indicated no significant differences between the groups on any of the outcomes.

Stepwise selection model analyses indicated that the G + C content of CDSs are the most important factor responsible for codon bias (R = 0.6831, P< 0.0001).

Longitudinal mixed model analyses indicated no significant differences between groups on any of the primary, secondary, or other outcomes (table 2).

Stepwise selection model analyses indicate that G + C content of coding sequence is the most important factor for codon bias.

The results of the animal model analyses indicate that additive genetic variance accounts for 44% and 39% of phenotypic variance in body mass in Longshanks Lines 1 and 2, respectively (Additional file 5: Table S5, Additional file 6: Table S6 and Additional file 7: Table S7).

The results of our structural equation modeling analyses indicated significant direct paths between attachment to all figures under the investigation and career decision-making process at Time 1.

Rasch modeling analyses indicated that the CANS-Trauma had good scale properties overall, including item fit within each of the domains.

Structural Equation Modeling analyses indicated that the SR latent factor predicted both measures of students' achievement significantly, but the SD factor did not predict either achievement measure significantly.

My modelling analyses indicated that two variables influenced positively (i.e. the presence of lizards (LIZ) and of tall grass (GRS)), and one influenced negatively (the presence of water bodies (WBS)), the African species' presence.