Sentence examples for be compared across models from inspiring English sources

Note that some parameters could not be compared across models; therefore, we investigated whether the patterns found in each model led to similar conclusions regarding PD.

20 Most importantly, however, formatively specified latent variables cannot be compared across models because their empirical realisation depends on both the indicators and the other variables within a model.

Unlike classical p-values, the Bayesian ppp-values are not necessarily uniformly distributed under the null hypothesis and should not be compared across models or be used to set a permissible type I error rate (false rejection of the model, [ 65]): there is no "critical value" such as 0.05 with ppp-values.

Differences in the strength and direction of climate change signals are compared across models and between bias correction methods, the statistical significance of climate change is tested as it evolves over the 21st century, and the impact of choice of reference and change period lengths is analysed as it relates to assumptions of stationary in current climate and change signals.

Continuity scores were compared across models using multilevel regressions.

To identify factors that accounted for household clustering of the infection, the coefficient for the household random effect was compared across models that included subsets of the study variables.

Another indicator was also provided in which the MAPE is divided by the mean of cost, so that the MAPEs could be compared across the models with different means of cost.

Preferences will be compared across discrete choice models via an assessment of correlations of the model coefficients and a comparison of the predicted MRS between attributes.

Preferences will be compared across discrete choice models (eg,older people vs informal carers vs staff) using two methods (1) correlations of the model coefficients and (2) by comparing the predicted MRS between attributes.

Preferences will be compared across discrete choice models (eg, decision-makers vs public, prejury vs postjury) using two methods: (1) using correlations of the model coefficients 29 and (2) by comparing the predicted MRS between attributes.

Randomization was performed before each fit, and this shuffle-and-fit procedure was repeated 50 times to generate a distribution of model log-likelihoods and BIC values against which the normative model could be compared across subjects.