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We used multivariate models to examine state-level factors associated with the capacity to serve children with ASD.Fifty-two of the 57 coordinators (91%) responded to the survey.
To build multivariate models to assess correctly and efficiently the contribution of tumor characteristics on the rate of regression of choroidal melanomas after brachytherapy in a way that adjusts for confounding and takes into account variation in tumor regression patterns.
Based on this design it was possible to analyse not only the standard univariate twin model but more powerful multivariate models to estimate the genetic and environmental sources of variance on phenotypic individual differences.
We also examine the correlation between these overlapping identities and test multivariate models to explain each identity using a common set of predictors: age, education, time in region, sex, political ideology, and race.
Patients were also analyzed in univariate and multivariate models to identify factors associated with successful conversion.A total of 21,672 unique instances of percutaneous trials were identified.
Goodness-of-fit statistics indicate a limited ability of the multivariate models to predict admissions, suggesting that variables not included play a role.
However, the variables sex and age were always maintained in the final multivariate models to account for possible remaining confounders.
Variables exhibiting association with outcomes at a bi-variate risk ratio (RR) of ≥1.5 or ≤0.60 or at a p-value of <0.10 were advanced into multivariate models to control for confounding and to estimate the independent impact of each factor on PTLC.
We then developed multivariate models to predict subarachnoid haemorrhage.
We used two multivariate models to adjust for potential confounders.
All studies used multivariate models to adjust for potential confounders.
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CEO of Professional Science Editing for Scientists @ prosciediting.com