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The Cox proportional hazards regression model in multivariate analysis was used to analyze the significance of various clinicopathologic parameters.

The significance of various variables for survival was analyzed by the Cox proportional hazards model in multivariate analysis.

For building the model in multivariate analysis, we selected variables with an external clinical judgment among those with a P ≤ 0.20 in univariate analysis.

Not included in the multivariate model In multivariate analysis controlled for all covariates significant in previous model as well as age and survey year, only alcohol consumption and school achievement were statistical significantly associated with the unawareness (Table 2).

Not included in the multivariate model In multivariate analysis controlled for all covariates significant in previous model as well as age and survey year, alcohol consumption, educational career and family structure remained statistically significant (Table 3).

Further, SEM, known as the integrated model in multivariate statistics, was employed to verify the synthesized relationship among job satisfaction, occupational burnout, and turnover intention, treated entirely as congregated latent concepts for the first time.

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Haufe, S. et al. On the interpretation of weight vectors of linear models in multivariate neuroimaging.

We discuss a general approach to dynamic sparsity modeling in multivariate time series analysis.

Encompassing univariate models in multivariate time series: A case study (joint with A. Mathis), Journal of Econometrics, 61(2), 197 233, 1994.

Whilst to our knowledge attitudinal and demographic predictors of MMR uptake during catch-up campaigns have not previously been modelled in multivariate analyses, the present findings may be usefully compared with the few relevant models predicting routine MMR uptake.

Significant factors were subsequently modelled in multivariate logistic regression analyses to estimate the OR of nurses' WPV experience.

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