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One or two-factor ANOVA, or the paired student t test was used to test for significance differences between sample categories.
Within each of the six multimorbid groups, the regression coefficient was tested for significance differences from their respective reference category with cost allocation as zero (0).
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"**" and "*" stand for significance difference at 0.01 and 0.05 probability levels, respectively.
For statistical significance, differences between two experimental groups were examined using Student's t-test, and Dunnett's test was used for multiple comparisons with control group.
The level of significance for significant difference between groups was set at P <0.05 in all analyses.
This approach allowed testing for significance of differences in survival, after accounting for differences in distribution of subgroups, based on P-values for the population parameter estimate.
Results were tested for statistical significance difference using Chi-square and Mann-Whitney test.
We used Fisher's exact test for significance of differences.
The Mean-Whitney U test was used for testing for significance at differences in outcomes between dichotomous characteristics.
Data were analyzed for significance of differences between means with Duncan's test at P < 0.05 (Two-way ANOVA).
We used Student's t-test, Pearson Χ2 and Mann Whitney tests for significance of differences, and Spearman or Pearson correlation coefficients for associations.
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