Sentence examples for test of inconsistency from inspiring English sources

Heterogeneity in each meta-analysis was assessed using a Chi test of heterogeneity, with a P value < 0.10 used to indicate statistical significance, and using the I test of inconsistency, with a value = 50% indicating substantial inconsistency.

Heterogeneity was assessed by determining the Cochran Q-statistic and by the test of inconsistency (I 2 ) [ 20], with a P-value < 0.05 or I 2  > 50% suggesting significant heterogeneity [ 21].

Comparing active treatments in such a network relies not only strongly on the questionable transitivity assumption but also precludes reliable testing of inconsistency.

Beyond-chance test evidence of inconsistencies between the structural equation model and the data demands diagnostic investigation of what might have gone wrong: in the data, in the modeling process, and/or in the theory itself.

The model initially included these three main effects, as well as sample-date × sex and sample-date × age interactions, to test for inconsistency in the effects of sex and age across the two sample dates.

For revascularisation, 95% credibility intervals of four loops did not overlap the null, three involving coronary artery bypass grafting, again with a positive overall test for inconsistency (P for inconsistency <0.001).

However, gene sets from two class direct comparison methods (t-test and Mann-Whitney test) show certain degree of inconsistency and discrepancy between lymph node phenotypes and gene expression patterns.

Although the performance of the z-test for inconsistency might vary according to the method used to estimate the uncertainty of the overall mean treatment effect, the power remains generally low for the loop of evidence that typically features in networks of interventions.

Equation (1) suggests that the method used to estimate the variance of the direct treatment effects and will play an important role in the performance of the z-test for inconsistency.

The I test is a measure of inconsistency describing the percentage of total variation between studies that is due to heterogeneity, with larger percentages indicating increasing heterogeneity [ 11].

Moreover, a suitable definition of factors and effects allows devising significance tests for inconsistency.