Examples of using The linear regression analysis in English and their translations into Portuguese
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In the linear regression analysis, age and 24-hour ClCr were significantly correlated R=0.28, p.
In this regard, we call attention to the power value,which shows the reliability obtained in the linear regression analysis.
For this reason, the linear regression analysis could be performed with the three models in a single group of force-closed stems.
Due to this, they were excluded, so as not to compromise the value of the adjustment R. In the linear regression analysis, the R value was 0.939, which is statistically significant Figure 3.
The linear regression analysis showed an association between the atheromatous plaque components and coronary artery remodelling.
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To check for the existence of correlation and its strength between the patient's age and the attributed risk classification level,Spearman's non-parametric correlation test and the linear regression analysis tests were used, respectively.
From the linear regression analysis was possible to identify that the years of schooling exerted considerable influence on the results of the verbal scale of the. .
While the intervention explained 5% of the variability of the proportion of adherence measure, the linear regression analysis showed that the Intervention was not able to explain the variability of the general and specific HRQoL measures.
The linear regression analysis of all data recorded in the moments considered critical revealed a weak correlation between two variables.
However, since no significant differences were found in comparing the deformations before andafter reimplantation, in any of the extensometer positions for these two test bodies, and since the linear regression analysis presented strong correlation, we decided to conclude the experiments with only two test bodies per group.
In the linear regression analysis, the three models were put together in a single group and the number of test bodies for this analysis thus increased to six.
To characterize temporal trends, we transformed the logarithmic coefficients Y,as it facilitates to reduce the heterogeneity of the residual variance of the linear regression analysis, that is, the values of the difference between the points of the mean line and points of the time series.
The linear regression analysis showed that only two variables(per capita family income and maternal years of schooling) had a significant influence on child height-for-age.
Categories were created and, among them, there was the linear regression analysis multiple variables that hype, sales and profits of product/ service lines, consumer value perception, communication program and develop product/ service appropriate the market are consistent influence factors on what students consider to be your.
The linear regression analysis applied to the dataset in the proposed prediction model had good power to explain the model r=0.68; R=0.46 Table 2.
The linear regression analysis comparing the 6MWT to the total IPAQ scores selected only the 6MWT as being determinant of 26.5% of the total variability of SPD.
However, the linear regression analysis comparing the 6MWT and the total IPAQ score selected only the 6MWT as being determinant for the total variability of the SPD.
In the linear regression analysis, it was noted statistical significance only for the professional category p= 0.001 and the orientation for performing the transfusion process p.
The linear regression analysis of JADAS-71, 27 and 10 and DAS 28 resulted in conversion formulas among the scales, the regression analysis of which is shown in Fig. 1.
In the linear regression analysis, FEV1 and FVC both in% of predicted were negatively associated with the time between the first diagnosis of tuberculosis and the completion of treatment mean time, 51.8 months.
In the linear regression analysis, the variables gender, age, level of education, previous use of antibiotics, HIV status, site of first medical visit, and radiological extent of tuberculosis showed no associations with longer time from entry into care to diagnosis or to treatment initiation.
On the other hand, the linear regression analysis showed that the strength of the association between age predictive variable and risk classification is very small and showed to be insignificant to change the risk level attributed in clinical practice.
In the linear regression analysis, it is noticed statistical significance associating the overall score and the Transfusion Step with the predictor variables"Professional category" p 0.001 and"received training and/or guidance for carrying out the transfusion process" p.
For the linear regression analysis, five predictor variables were considered: received training or guidance to perform blood transfusion; participate in specific training on blood transfusion; professional category; number of blood transfusions/month; and length of professional practice.
The linear regression analyses to determine the association between negative life events and social anxiety score are presented in Table 3.
The linear regressions analyses showed that the TP and TN were negatively related to%MVS during all periods sampled.
From 1986 to 1995 no decrease was observed in the infant mortality nor in its neonatal orpost-neonatal components in the municipalities within the MRBH within this period the linear regression analyses presents values that are not significant for beta.
We found that use of insulin therapy was correlated with the score on the emotional burden subscale of the B-DDS,but the results from the linear regression analyses showed that its variables were very weak predictors of diabetes-related distress R=0.13.