Sentence examples for regression introducing from inspiring English sources

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Main effects and interactions that remained significant on a 0.05 level were included in the final multivariate multilevel regression introducing hospital ward and hospital as levels 2 and 3 variables.

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Second, the random forest algorithm for quantile regression introduced in [9] produces the same tree structure as the usual random forest algorithm and only changes the way in which predictions are generated for the leaf nodes.

(ii) Random forest imputation is based on random forest regression introduced by Breiman [ 29].

The unknown constants c ≡ (c1,..., c m ) may be estimated by reverse logistic regression introduced by Geyer [ 46].

16We have also estimated the same regressions introducing wage as a control variable and reach similar conclusions.

We investigated the presence of a dose-response relationship between the number of joints smoked per week and the natural logarithm of the APRI score with a linear spline regression model, introducing flexibility to linear regression by allowing the slope of the curve to change at the prespecified knots.

For multivariate analysis we performed a logistic regression model introducing gender and age to correct deviations due to theses two factors.

Furthermore, a Fit Statistic (AIC, Akaike's Information Criterion) was calculated for the logistic regression model, introducing the clinical risk factors in a stepwise fashion.

At the multivariable level, we explored the associations between socio-economic disadvantage in early childhood and developing disabling chronic conditions up to 10 years later using multiple logistic regression modelling, introducing sequentially potential confounders of the association (age, sex, ethnicity and family status).

In order to assess the potential heterogeneity of the impact of the program on various groups of individuals, we consider separately five dimensions (gender, age, education, marital status and ethnicity) and re-run regressions by introducing interaction terms with the 'treatment x year' variable for each dimension.

In this study, it gave individual patients different weights according to their probabilities of living longer than the median time from diagnosis to Tx2; therefore, the biases of the regression estimates introduced by patients' mortality risks were reduced by the IPW Cox regression framework.

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