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Principle component analysis (PCA) was implemented to verify the distribution of variables for study groups, as well as confirm the time trend of variable changes.
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Tendency value represents the linear trend of variables, that is, the rate of increase or decline.
Figure 1 shows the trend of variables in their logarithm form from 1981 to 2012.
The medians of the quintiles were fit as continuous variables to estimate the trend of variables across quintiles in a linear regression model (adjusted R = 0.99, B = 900 cells/mm per quintile, P = 0.001).
A general linear model was used to assess the age-adjusted means and proportions of the population's characteristics across quintiles of triglyceride levels and to fit the median of the quintiles as a continuous variable to estimate the trend of variables across quintiles.
Fig. 1 Plots of trends of variables in their logarithm forms.
Kitchin (2014: 106) has described how 'visual methods effectively reveal and communicate the structure, pattern and trends of variables and their interconnections,' thereby enabling users to navigate and query data, gain an overview of entire datasets, zoom in on items of interest, view relationships, and monitor the real-time dynamics of a phenomenon.
Continuous traces exhibit smooth trends of variables regularly observed at continuous time-scales.
Repeated-measures ANOVA was used to estimate the time trends of variables shared between full remission and episode.
Our mathematical analysis shows that the observed time trends of measurable quantities from particular subgroups of infected persons (such as primary drug resistance in monitored subpopulations) can correspond to different and unexpected time trends of variables of critical public health interest that are not measured directly in the general population.
In this regard, P values of 0.05 or less for each variable indicated discrepancy in the time trend of the variable between the two groups.
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