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Even if variance parameters are of interest, it is not advised to use the Wald test when evaluating variance components.
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The significance of the independent variables was estimated using the Wald test.
The causal impact of selected monetary and fiscal determinants on interest rates from the VAR model has further been studied using the Wald test of Granger causality.
A stepwise backward process was then performed until all p values were <0.05, and models were compared using the Wald test.
Statistical significance was assessed using the Wald test.
[11] We investigated model misspecification by examining the significance of added quadratic terms using the Wald test, and we assessed model calibration using the Hosmer-Lemeshow test.
The multivariate Cox models were obtained by stepwise forward inclusion of the covariates and statistical significance of the model was analysed using the Wald test.
Starting with the 11,515 probe sets remaining from the data filtering process, we identified a subset of informative probe sets that were best correlated with survival time using the Wald test from the Cox proportional hazards model.
Further Fourier terms were found to have no significant effect, and trends were fitted either as a linear term or a linear term plus categorical term stratified by year, with significance evaluated using the Wald test.
Regression was tested using the Wald test.
Interactions were assessed using the Wald test.
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