Sentence examples for model for summarizing from inspiring English sources
Models include a first-level general linear model (GLM) analysis for fMRI data, a GLM implementation of the simplified reference tissue model (SRTM) with time-varying changes in "binding potentials", a second-level random-effects of mixed-effects model for summarizing first-level GLM analyses, and fitting functions for performing common fits of MRI data (e.g., T1, T2, ADC, DTI, …).
The diagram is utilized to find a logical relationship between the constructs from the evidence, and simplify the paradigm model for summarizing phenomena as the logic line of "conditions - action/interaction - result".
cn.FARMS presents a probabilistic latent variable model for summarizing probes to obtain raw CN estimates.
We propose a method for constructing multiple testing procedures using the closed testing procedures and the random-effect model for summarizing estimated values of parameters.
In this study, we present the multilevel model (the two-level and the three-level models) for summarizing single-case results over cases, over studies, or both.
Microstructural models for summarizing the preferred chain orientation and anisotropic features were given in Figures 7(a)– 7(c) for each product.
In addition to estimating AUC for summarizing the model's discrimination, we used the Hosmer and Lemeshow test to test for goodness of fit and calibration.
In addition to estimating AUC for summarizing the model's discrimination, we used the Hosmer and Lemeshow test to determine the goodness of fit and calibration.
We advocate the use of related effects models in large meta-analyses for summarizing the evidence for association across independent studies of related phenotypes.
The proposed technique is designed using semantic similarity based clustering and topic modeling using Latent Dirichlet Allocation (LDA) for summarizing the large text collection over MapReduce framework.
Our aim was to improve meta-analysis methods for summarizing a prediction model's performance when individual participant data are available from multiple studies for external validation.
