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This paper describes approach based on active scripts models that controls and restrict personnel activities on controlling technological processes.
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In regression models that controlled for confounders, which included very low birth weight, magnesium remained a significant risk factor (adjusted odds ratio, 3.7; 95% CI, 1.1-11.9; P =.03).
Conventional software engineering approaches and even standard languages compose web services as workflow models that control the business logic required to coordinate data over participating services.
They are far less complex than most of PHY models that control the same amount of communication parameters.
Nevertheless, logistic regression models that controlled for the 10 most statistically significant Class II SNPs, as well as the 8 Class III SNPs identified in this study, demonstrated an independent allelic contribution of rs4959039 to MS susceptibility.
Odds ratios are from random effects regression models that controlled for the number of hospitalizations.
p-values are from mixed effects logistic regression models that controlled for the number of hospitalizations.
In the majority of cases, the models that controlled for unobserved heterogeneity estimated higher educational differences in mortality than the models that did not control for it.
Moreover, when compared with the AIC, the models that controlled for unobserved heterogeneity gave a statistically significantly better fit than the models that did not control for it.
The same result was obtained in regression models that controlled for whether the patient saw a physician or non-physician specialist, and in models that controlled for change in health status.
Adjusted estimates of risk were obtained with multivariate models that controlled for H. pylori infection, and other covariates listed above.
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