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The overall IEQ acceptance is calculated from a multivariate logistic regression model.
Second, we studied the impact of correcting for such measurement error on bias and precision of odds ratios from a multivariate logistic regression model.
Odds ratios (OR) and 95% confidence intervals (CI) from a multivariate logistic regression model were, respectively, 0.389 (0.156–0.971) and 0.724 (0.533 0.985).
In conclusion, our study demonstrates that: 1: A linear combination of blood tests based on Z scores for PTH, PO4, and albumin derived from a multivariate logistic regression model correlates significantly with in-patient hospital payments (HCH) exceeding $3,000 in one or more months over a 13 month study period at p < 0.005.
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ExprTarget is inspired by a multivariate logistic regression model for a binary outcome and predictor variables from existing computational solutions.
A multivariate logistic regression model evaluated the predictive power or synergism gained from linear combinations of parameters.
Risk factors were evaluated by a multivariate logistic regression model.
A multivariate logistic regression model was applied.
A multivariate logistic regression model was performed.
Analysis was performed using a multivariate logistic regression model.
The groups were compared using a multivariate logistic regression model.
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