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To study the association between the main variables collected in the comprehensive geriatric assessment (CGA) and mortality, in a clinical cohort of elderly people referred from primary care, following standardised criteria, to a geriatric unit.
Wilcoxon's test for paired samples was applied to identify differences between the main variables of patient acceptance for all three tests.
In addition to the three main explanatory variables (sample type, route of infection, age) all two- and three-way interactions between the main variables were also included in the statistical models.
Pearson correlation coefficients were calculated between the main variables.
A bivariate pairwise correlation analysis was performed to explore relationships between the main variables.
Survey results were analysed using PASW 18. Descriptive and bivariate analyses were used to analyse relationships between the main variables of interest.
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Nowadays, monitoring process is simply to ensure about preserving the steadiness of the relationship between the main variable of interest (output) and one or more environmental variables or control variables (inputs) over the time, hence the application of classical SPC is not convenient.
We tested for interaction by fitting interaction terms between the main variable of interest (Aboriginal or Torres Strait Islander status) and all factors that were found to be statistically significantly associated with food insecurity.
Potential confounding variables were considered for inclusion in the models based on a priori criteria: significance in previous work, significant contribution to the model fit (P value of the Wald χ <0.05), or confounding the association between the main variable of interest and the outcome by more than 10%.
We saw no significant interaction between any of the main variables in the final model, and plots of model residuals indicated that these associations were approximately linear.
High correlation is on the other hand found between two of the main variables, MaxNDVI and SINDVI with distinct grouping of the vegetation types along the possible regression line – dry types at the bottom and more moist and vigorous types at the top rigth.
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