Sentence examples for models that correct from inspiring English sources
Analysis was conducted using spatial stochastic frontier models that correct for heterogeneity and spatial interactions between sub-national units.
Linear mixed models that correct for confounding by the genetic background using a kinship matrix calculated from genetic data were used throughout (Kang et al., 2010; Segura et al., 2012).
Understanding the accuracy of self-reported data and developing prediction models that correct for underreporting of hypertension in self-reported data can be critical tools in the development of more accurate population level estimates, and in planning population-based interventions to reduce the risk of, or more effectively treat, hypertension.
In future, it may be feasible to develop universal models that correct for sensitivity/specificity differentials of the methods used to test for infection, preferably based on large-scale population surveys which have used both RDT and microscopy for the same individuals with the appropriate quality assurance and external validity.
Assessing the validity of self-reported data in estimating hypertension prevalence in specific geographic areas, and developing simple prediction models that correct for possible miss reporting of HBP in self-reported data, can be essential to the creation of accurate population level estimates, and for population level efforts to effectively prevent or treat HBP within particular contexts.
Comparisons of repertoire size between the first and second dawn chorus recorded in the framework of the playback experiment and between years were done using Linear Mixed Models (LMM) that correct for non-independence of the data.
Current screening approaches are unable to identify all altered samples, whilst models that attempt to correct for 'open-system' behaviour are not applicable across all diagenetic scenarios.
The models that did not correct for ILS substantially overestimated duplications and transfers.
The safety effects of signal spacing and street network pattern were estimated for this study based on 118 meso-level units obtained from 21 urban arterials in Shanghai, and were examined using CAR (conditional auto regressive) models that corrected for spatial correlation among the units within individual arterials.
The same results were obtained in models that corrected for infliximab dosage and/or concomitant corticosteroid, MTX, or leflunomide use by adding them as (non-significant) covariates to the mixed models analysis.
Adjusted deviance using the 3 correct predictors (based on methodology summarised in Figure 1) was highest for the model that used correct (i.e. true) absences (0.987).
