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Determining whether the correlation level is low enough to consider relocations as being statistically independent is relatively easy [30].
Therefore, in order to avoid erroneously excluding non-ignorable clustering from the analysis, we suggest that the ICC should be assumed to be non-zero unless there is evidence to the contrary or strong reasons for suspecting it is 0. Determining whether the correlation between patient assignments within clusters is non-zero depends on whether the clustering is pre or post-randomisation.
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We then resolve contributions from different length scales in the genome – determining whether the correlations are due to broad regional similarities, or just the singular behavior of individual repeat elements.
To determine whether the correlation between corneal power (K) and axial length (AL) can be used for intraocular lens (IOL) power calculation when biometric data are incomplete.
To determine whether the correlation was consistently positive during the delay period, we analyzed the sum of the correlation values across time-shifts during the delay period and found that it was significantly different from zero for the 0.3 4 Hz sub-band of PMd data (t-tests with p<0.0001 for both monkeys).
We simulated human demography under a model in which the recombination rate was the same for all the simulated populations, and we sought to determine whether the correlation between genetic distance and inferred recombination similarity between simulated populations was similar to the observed in empirical data.
The Pearson correlation test was used to determine whether the correlation between two parameters was significant.
Descriptive analyses were used to investigate the agreement between the two procedures using the Bland and Altman method to determine whether the correlation between ABI readings varied systematically.
TRE analysis was used to determine whether the correlation clustering could be interpreted in terms of the actions of networks of transcription factors.
We performed a multivariate Cox regression analysis to determine whether the correlation of C/EBPα with patient survival was confounded by underlying clinical parameters.
To determine whether the correlation matrix was factor analysable (36), Bartlett's Test of Sphericity had to be significant, while the Kaiser Meier Olkin measure of sampling adequacy had to be above the recommended value of 0.6 (37).
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