Sentence examples for mapping models were from inspiring English sources

Seven different mapping models were tested for the best fit of each trait.

Both mapping models were initially fitted using random intercepts generalized least squares (GLS) models.

The mapping models were able to explain approximately 63%–65% of the variation in the observed utility scores.

Using baseline data various mapping models were developed, where WOMAC scores were used to predict the EQ-5D scores.

Using a previous database, mapping models were created by estimating the relationship between the Health Assessment Questionnaire [ 42] and the utility measures of the EQ-5D [ 30], SF-6D [ 43], HUI2 and HUI3 [ 32].

The four created mapping models were then used to estimate the QALY gain associated with the two different drug strategies in a different data set, where the results for the two treatments were 3.33 and 4.67 for the EQ-5D mapping model, 3.79 to 4.69 for the SF-6D, 4.16 to 5.33 for the HUI2, and 1.73 to 3.68 for the HUI3.

Second, different mapping models are built in the neighborhood of the center of different holes.

The purpose of this paper is to examine whether mapping models are reliable and accurate in terms of their predictions for a large and varied patient dataset.

Individuals and organizations who have generously contributed unpublished data for use in the mapping models are listed at http://www.map.ox.ac.uk/acknowledgements/.

For 19 mapping algorithms, the number of observations used to estimate mapping models was not clearly stated: generally as repeated observations of an unstated number of participants were included in the estimation sample.

A discrete-time iterative nonlinear mapping model is derived.