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The lagged effects of all these climatic variables were incorporated in the next regression analysis.
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For these reasons, we turn next to regression analysis so we can control for other important correlates with migration decisions and directly examine the impact of local economic shocks.
Next we used regression analysis to test each of the candidate baseline correlates, using the independent 2005 dataset that includes a total of 56 adult and child participants.
We next performed multivariable regression analysis in order to identify factors with independent associations with hs-TnT.
We have next performed a regression analysis in which we combined data for all buried and all solvent-exposed mutant proteins, respectively.
we next performed a regression analysis on the PET data (i.e., T1 and T2 metabolism vs. T1 and T2 accuracy) (Table 2).
We next performed multivariate regression analysis using these variables and found that the estimated influence rate per unit change in each variable on HbA1c was as follows: baseline HbA1c, -0.489; baseline BMI, 0.016; diabetes-drug administration, 0.176; rate of change in TG, 0.004; and rate of change in TC, 0.005.
Analyzing potential therapeutic consequences such as need for surgery, we next conducted a logistic regression analysis with R, using the need for surgery as dependent variable, and the SNP genotype as independent variable, taking localization as well as behaviour as covariates.
Next we used logistic regression analysis for clinical symptoms reported by patients to verify their association with Cryptosporidium spp infection.
To account for potential confounding factors, we next performed multivariate logistic regression analysis to examine the likelihood of prolonged pregnancy with increased maternal BMI at booking (Table 2).
We next performed a multiple regression analysis with cued and uncued semantic distance variables from the verb generation task included as predictors of creativity (factor scores).
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