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Wall to floor ratio and the number of basements were identified as the model predictors with a model fit of 48.1% (R2).
To partially mitigate the impact of multicollinearity on the estimation of relative contributions to HRQoL within the same model, predictors with (absolute) correlations exceeding 0.7 were not included in the same multivariate model.
Perform a single Tobit regression (Tobin 1958) of 3PBA left-censored at the detection limit on all step 2 nondiet predictors, and select those predictors with p-value ≤ 0.2 for inclusion in the final model (predictors with p-values > 0.2 we manually removed from the step 3 regression until all remaining predictors had p-values ≤ 0.2).
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These indicate that the RES based model predictor with higher R2 and less RMSE performs better than the other models.
Our model predictors are consistent with previous findings.
Covariates for each model were selected using Bayesian model averaging; predictors with posterior probabilities >35% were retained in the model (13).
The seven scales of TCI were entered in a standard multiple regression model as predictors, with the RoD as dependent variable.
Within each region a user specified predictive model associates the predictors with the response.
The final model included only predictors with significant contribution (p<0.05).
The final model included only predictors with a statistically significant contribution (P<0.05).
Second, we used regression models to examine predictors, with a keen interest in spatial and combined spatial with math predictors of math performance.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com