Sentence examples for exploratory latent from inspiring English sources

Exploratory Latent Class Analysis was used to uncover latent constructs within the 15 dizziness descriptors and 11 dizziness triggers.

Initially, we performed exploratory latent class analyses (LCA), a statistical technique suitable for finding meaningful subgroups in a population, which are similar, for example, in their growth trajectories.

Here we present an exploratory latent class analysis of CAM use among breast cancer patients who participated in the Long Island Breast Cancer Study Project [ 20].

In recognition that conversations are complex phenomena, we will conduct exploratory latent class analyses [ 51] to examine whether observed patterns among the individual domains (i.e. ENGAGING, RESPONDING, INFORMING, and FRAMING) suggest "clinical types" of conversations that are predictive of outcomes.

While this is an accepted approach in health economics in the context of priority setting, 38 the exploratory latent class analysis in this study suggests that the preferences of an obese population around priorities for bariatric surgery may differ to those of the general public.

The p value shows that model 7 is sufficient to end the exploratory analysis with seven latent classes, given a 0.001 alpha level.10 Since the subjective social class is measured by a five-category dummy, we chose the five-category variable generated from model 5 to compute status discordance and report the estimated conditional probabilities of the five latent classes in the Appendix.

Factor analysis (FA) can be applied as a data-reduction-tool without any a-priori assumption regarding associations between observed data and latent structure (Exploratory Factor Analysis, EFA).

As it is exploratory and quickly identifies latent spatial fields, it may be considered a screening tool for identifying candidate cancer sites that should be included in a joint disease mapping analysis.

Factor analysis (FA) has been widely applied in microarray studies as a data-reduction-tool without any a-priori assumption regarding associations between observed data and latent structure (Exploratory Factor Analysis).

We used exploratory factor analysis (EFA) and latent class analysis (LCA) on ICD-11 nicotine dependence proposed criteria to explore dimensionality and phenotypes profiles, followed by logistic regression models to examine the association between latent classes and socio-demographic, psychiatric and chronic medical conditions.

Jigar khun was by far the dominant latent variable in exploratory and confirmatory models of ASCL scores, suggesting that it represents a specific cultural syndrome rather than simply an idiom of distress.