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For each Table 1 variable, significance of the estimated hazard ratio was not altered within any bivariate Cox PH model, with only two exceptions.
Whether this inconsistency is a result of genetic evolution in vitro or a true reflection of variable significance of CD133 expression in the original tumors remains to be determined.
A forward stepwise multiple linear or logistic regression analysis was used, with a required variable significance of 0.05 to be included into the model, and a cut-off value of 0.1 for exclusion.
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Within the coelomates, the coelom has been of variable significance to the form and diversity of the various phyla.
Comparisons were calculated using non-parametric tests for categorical variables and independent samples t tests for continuous variables (significance level of α = 0.05).
A descriptive quantitative analysis was performed; the chi-square test was used to analyse the association between variables (significance level of p < .05).05
A backward stepwise method was used, and at each step, the least significant variable was eliminated, until all the remaining variables had significance of less than 0.05.
All variables were entered as a series of indicator variables, the significance of which was tested using the likelihood-ratio test of goodness-of-fit (significance, P⩽0.05).
However, with the addition of even one or two of the remaining variables, the significance of this association was lost.
High canonical loading of a particular variable indicates the significance of that variable in the interpretation of the canonical variate.
Inclusion of the time variable reduces the significance of the exposure variable.
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