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Statistical significance of the regression coefficients was tested by using the Wald likelihood ratio test.
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P values for individual covariates were calculated using the Wald test and the likelihood ratio test for the overall model.
Confidence intervals and associated P values were computed for the estimated parameters based on the asymptotic normality of maximum likelihood estimators and using the Wald χ statistics in the SAS Genmod procedure.
Statistical significance was assessed using the Wald test statistic, and no approximation to the likelihood in the event of tied failure times was utilised.
Both the Robust Poisson method using the Wald test and the log-binomial method using the likelihood ratio test almost always had acceptable size, but the log-binomial method generally had higher power.
Model parameters were estimated by using the maximum likelihood method; their statistical significance was assessed by using the Wald statistic (8 ).
Linear trends were tested using the Wald test.
Statistical significance was assessed using the Wald test.
Interactions were assessed using the Wald test.
Regression was tested using the Wald test.
* significant at the 5% level using the Wald test.
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