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During multivariate logistic regression model fitting, significant independent variables associated with seeking pre-travel health advice differed for Australian travelers, other Western travelers and Asian travelers and separate models were developed.
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Variables were subjected to model fitting if significant at a chosen α = 0.05 and smallest cell frequencies proved sufficient for stable multivariate analyses.
The results were fitted to significant models.
Equivalent electrical networks can be designed which contain the minimum of circuit elements to fit the significant details in the experimentally obtained Bode diagram.
The blue line is the linear regression line computed by least squares fit with significant P value < 0.05.
The difference in fit between the models with a common γ and with individual values fitted is significant (Χ2=5.04, p<0.02 on a one-tailed test).
In New South Wales, Australia Bayesian models that adjusted for stage of disease were fitted and significant variation in prostate cancer survival between regions was found.
This weighting factor emphasizes fitting in more significant spectral ranges and de-emphasizes fitting in less significant wavelength ranges.
The lack of fit values for all models was not significant, showing that the fitted models are significant.
Since all further measures of model fit (RMSEA, CFI, TLI) indicated very good model fit, the significant χ 2 -statistic can be neglected.
The "Lack of fit F-value" of 12.00 implies that the lack of fit is significant.
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