Results 21 to 30 of about 168,229 (311)

Disease comorbidities associated with chemical intolerance

open access: yesEnvironmental Disease, 2021
Background: Chemical intolerance (CI) is characterized by multisystem symptoms initiated by a one-time high-dose or a persistent low-dose exposure to environmental toxicants.
Raymond F. Palmer   +5 more
doaj   +1 more source

Latent Class Growth Modelling: A Tutorial [PDF]

open access: yesTutorials in Quantitative Methods for Psychology, 2009
The present work is an introduction to Latent Class Growth Modelling (LCGM). LCGM is a semi-parametric statistical technique used to analyze longitudinal data.
Benoît Louvet   +4 more
doaj  

Class proportions and class-specific probabilities from a four-latent-class model of chronic conditions.

open access: yes, 2022
Class proportions and class-specific probabilities from a four-latent-class model of chronic conditions.
Katherine Keenan (543406)   +4 more
core   +1 more source

The Latent Class Twin Method [PDF]

open access: yesBiometrics, 2016
Summary The twin method refers to the use of data from same-sex identical and fraternal twins to estimate the genetic and environmental contributions to a trait or outcome. The standard twin method is the variance component twin method that estimates heritability, the fraction of variance attributed to additive genetic inheritance.
openaire   +2 more sources

Identifiability of Latent Class Models with Covariates

open access: yesPsychometrika, 2022
Abstract Latent class models with covariates are widely used for psychological, social, and educational research. Yet the fundamental identifiability issue of these models has not been fully addressed. Among the previous research on the identifiability of latent class models with covariates, Huang and Bandeen-Roche (Psychometrika 69:5–
Jing Ouyang, Gongjun Xu
openaire   +3 more sources

Class Enumeration and Parameter Recovery of Growth Mixture Modeling and Second-Order Growth Mixture Modeling in the Presence of Measurement Noninvariance between Latent Classes

open access: yesFrontiers in Psychology, 2017
Population heterogeneity in growth trajectories can be detected with growth mixture modeling (GMM). It is common that researchers compute composite scores of repeated measures and use them as multiple indicators of growth factors (baseline performance ...
Eun Sook Kim, Yan Wang
doaj   +1 more source

Characterizing longitudinal patterns of physical activity in mid-adulthood using latent class analysis: results from a prospective cohort study. [PDF]

open access: yes, 2011
The authors aimed to describe how longitudinal patterns of physical activity during mid-adulthood (ages 31-53 years) can be characterized using latent class analysis in a population-based birth cohort study, the Medical Research Council's 1946 National ...
G. D. Mishra   +11 more
core   +1 more source

Which Policies and Factors Drive Electric Vehicle Use in Nepal?

open access: yesEnergies, 2023
Electric vehicles (EVs) offer a viable technological solution for mitigating greenhouse gas emissions in the transportation industry, addressing pressing societal concerns regarding climate change, air pollution, and sustainable energy consumption.
Laxman Prasad Ghimire   +2 more
doaj   +1 more source

Latent Class Analysis and Latent Profile Analysis [PDF]

open access: yes, 2015
Latent class analysis (LCA) and latent profile analysis (LPA) are powerful techniques that enable researchers to glean insights into “hidden” psychological experiences to create typologies and profiles to provide better-informed community-based policies and practice.
Williams, GA, Kibowski, F
openaire   +1 more source

Incorporating Machine Learning Into Factor Mixture Modeling: Identification of Covariate Interactions to Explain Population Heterogeneity

open access: yesMethodology, 2023
Factor mixture modeling (FMM) has been widely adopted in health and behavioral sciences to examine unobserved population heterogeneity. Covariates are often included in FMM as predictors of the latent class membership via multinomial logistic regression ...
Yan Wang, Tonghui Xu, Jiabin Shen
doaj   +1 more source

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