Sentence examples for measures analysis revealed from inspiring English sources

Mixed models repeated measures analysis revealed significant differences between the study arms regarding total PANSS score change favouring n-3 PUFA (p = 0.016; effect size (ES) = 0.29).

The repeated measures analysis revealed significant strain by time interaction effects for relative warp four (P = 0.0072) and relative warp five (P<0.001), indicating that the change in these morphological metrics are different for each strain over time.

Log-rank tests and repeated measures analysis revealed a significant difference in dynamic serum MMP-3 between progressive and non-progressive patients.

After 8 treatment sessions for experimental group and follow-up test, the result of Repeated Measure analysis revealed that the effects of coping strategies training process on decreasing test anxiety remained significant (p < 0.05) for 4 weeks.

In terms of self-efficacy, the repeated measure analysis revealed a significant linear trend, F 1, 67) = 114.37, p < .001, η p  = .631, indicating an overall decrease in students' self-efficacy during the clinical reasoning task.

Use of continuous SES measures (RII analysis) revealed stronger evidence for an association between education and telomere length (SMD = 0.043, 95% CI: 0.011, 0.074; P = 0.008).

When the exit and entrance of the maze were displaced laterally, repeated measures within subject analysis revealed that mice needed significantly more time to find the new and correct exit (F 1,55) = 22.53; p < 0.001).

As before, FRAP measures for this analysis revealed no differences in LH dynamics following treatment with the PKC inhibitors, suggesting that PKC activity may not modulate LH mobility in the nucleus.

The shape of the particles as measured by SEM analysis revealed almost spherical in shape with relative smooth surface for all the formulations (Figure 2a).

Muscular activity and finger blood flow values are reported as the average of the left and right side for each region because ANOVA repeated measures analysis (rANOVA) revealed no side differences for the finger skin blood flow and muscle activity except for the frontalis muscle SEMG (left side (10.9 μV) > right side (9.2 μV); F(43) = 8.0, p = 0.007).

Across 48 measured behavioral phenotypes, QTL analysis revealed 27 loci with a P value < 4.48 × 10-6, corresponding to a genome-wide false discovery rate (FDR) of 5%.