Sentence examples for based on the logit from inspiring English sources

The first uses a linear model based on the logit transformation to convert the bounded soil water response range to unbounded form.

The probability (P i ) that the individual accepts an offer (A) based on the logit model, can be expressed as follows (Lee and Han 2002): {P}_i={F}_nleft(Delta Uright)frac{1}{1+ exp left -Delta Uright)}=frac{1}{1+ exp left -DeltaUrighta -upbeta mathrm{A}=frac{1}{thrm{Y}+upthexp mathrm{S}right)right}} (3).

Based on the logit model, risk of bleeding was found to be the most important factor in patient treatment preferences with a relative importance of 0.30, followed by risk of infection (0.28), fatigue (0.23), and frequency of transfusions (0.20) (Fig. 2; no statistical comparison of relative importance between attributes was conducted).

Compared with the method based on the logit model, this method has a higher sensitivity (+14%) and slightly weaker specificity (-3%).

We found that a transformation based on the logit function performed reasonably well at stabilising the variance (see online supplementary appendix for details and lookup table).

Consistency of SRH was a dichotomous outcome and logistic regression based on the logit function (logarithm of the odds) was performed with the predictive quasi likelihood second-order approximation procedures.

To select the optimal modality for single and multiple organ procurement, multiple comparison procedures (MCA, MCC, and MCB) were applied based on the logits from either the logistic regressions or generalized linear mixed models (GLMM).

The proposed design approach is compared with three non-adaptive design approaches, two aggregate-customization approaches (based on the conditional logit model and on a mixed logit model), and the (nearly) orthogonal design approach, under various degrees of response accuracy and consumer heterogeneity.

The VOSL model is established based on the binary Logit model.

Also, the empirical results based on the multinomial logit model show that the probability of households being in any of the identified food insecure states relative to food secure households decreases significantly and consistently with income, household size, whether households consume only purchased food, and the geographical region of the household.

Specifically, the M-moment score test is introduced and shown to be an attractive alternative to well known restricted-alternative tests, such as the row-means Cochran Mantel–Haenszel test, the Kruskal Wallis test, and the likelihood-ratio test based on the cumulative-logit row-effects model or the log-linear row-effects model.