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Variations in variables (χ2 and ANOVA) were considered statistically significant if p value was < 0.05.
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In addition, variations in variable values of work experience, political status, way of gaining entry to work, etc. also show that, from first job to the present job, a lot of changes occur to affect the overall characteristics of laborers.
Lastly, the characteristics that could explain variations in variable cost were analysed as a whole through a mixed linear model with logarithmic transformation of continuous variables (Table 3).
While fixed costs of survey implementation were similar for the two survey approaches, there were considerable variations in variable costs, resulting in an estimated annual cost saving of about US$45,000 under the integrated survey approach.
In biomedicine, hypotheses often concern variance structure patterns of variation in variables when group and population structure are controlled.
Table 4 gives some examples, including both our original and our updated sample size estimation, and shows the effects of variation in variables on the sample size.
Besides, an FE model identifies the effects from within variation in variable M, i.e., variation in the share of migrants across time.
Geochemical data were log-transformed (with the exception of pH) to minimize the significance of unit differences and the high degree of variation in variable values among samples.
Thus, overall, although putative pro-enzyme and putative enzyme domains seem fairly conserved, the extent of variation in variable domains 1 and 2 differs greatly among parasite lineages.
There was greater variation in variable importance for unstructured as compared to structured missingness.
The difference in variation of variable importance for simulated versus the resampled case study data provided evidence that data MCAR produces greater variation in variable importance.
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