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Basic assumptions underlying indirect comparisons include that results from different trials should be sufficiently homogeneous [ 61] by either fixed-effects models or random-effects models.

Pooled odds ratios (OR) with 95% confidence intervals (95% CI) were calculated using either the fixed effects model or random effects model.

In the future, guideline for using log-ratio transformation methods with linear regression, a generalized linear model or random forest should be developed and combined with ancillary variables to improve the interpolators.

In this case, it becomes possible to use the symmetric hopping model (or random barrier model), whereby the charge transfer is a jump between close equilibrium positions in non-periodic potential [19].

Pooled effect was calculated using either the fixed effects model or random effects model.

Pooled estimates of treatment effect were calculated using either the fixed effects model or random effects model.

During this process, we will choose an appropriate effects model, such as the fixed effects model or random effects model according to the heterogeneity.

Multilevel modeling (also called mixed-effects modeling, hierarchical linear modeling, or random coefficient modeling) is an advantageous method when handling dependencies in repeated measures data because incomplete data (ie, dropout) are easily accommodated.

The relative risk (RR) and 95% confidence intervals (CI) were estimated by the fixed effects model or random effects model to evaluate the correlation between COX-2 gene polymorphism and the risk of oral cancer.

Earlier studies also tend not to account for the panel nature of DCE data with serial correlation of choices between the same participants, which can now be adjusted for through an appropriate model or random effects specification.

Pooled odds ratio (ORs) and 95% confidence intervals (95%CIs) were calculated by either fixed-effects model or random-effects model based on heterogeneity test.