Search results for "latent variable model"
showing 10 items of 12 documents
Using latent variable models to identify large networks of species‐to‐species associations at different spatial scales
2015
Summary We present a hierarchical latent variable model that partitions variation in species occurrences and co-occurrences simultaneously at multiple spatial scales. We illustrate how the parameterized model can be used to predict the occurrences of a species by using as predictors not only the environmental covariates, but also the occurrences of all other species, at all spatial scales. We leverage recent progress in Bayesian latent variable models to implement a computationally effective algorithm that enables one to consider large communities and extensive sampling schemes. We exemplify the framework with a community of 98 fungal species sampled in c. 22 500 dead wood units in 230 plot…
Model‐based approaches to unconstrained ordination
2014
Summary Unconstrained ordination is commonly used in ecology to visualize multivariate data, in particular, to visualize the main trends between different sites in terms of their species composition or relative abundance. Methods of unconstrained ordination currently used, such as non-metric multidimensional scaling, are algorithm-based techniques developed and implemented without directly accommodating the statistical properties of the data at hand. Failure to account for these key data properties can lead to misleading results. A model-based approach to unconstrained ordination can address this issue, and in this study, two types of models for ordination are proposed based on finite mixtu…
Efficient estimation of generalized linear latent variable models.
2019
Generalized linear latent variable models (GLLVM) are popular tools for modeling multivariate, correlated responses. Such data are often encountered, for instance, in ecological studies, where presence-absences, counts, or biomass of interacting species are collected from a set of sites. Until very recently, the main challenge in fitting GLLVMs has been the lack of computationally efficient estimation methods. For likelihood based estimation, several closed form approximations for the marginal likelihood of GLLVMs have been proposed, but their efficient implementations have been lacking in the literature. To fill this gap, we show in this paper how to obtain computationally convenient estim…
Variational Approximations for Generalized Linear Latent Variable Models
2017
Generalized linear latent variable models (GLLVMs) are a powerful class of models for understanding the relationships among multiple, correlated responses. Estimation, however, presents a major challenge, as the marginal likelihood does not possess a closed form for nonnormal responses. We propose a variational approximation (VA) method for estimating GLLVMs. For the common cases of binary, ordinal, and overdispersed count data, we derive fully closed-form approximations to the marginal log-likelihood function in each case. Compared to other methods such as the expectation-maximization algorithm, estimation using VA is fast and straightforward to implement. Predictions of the latent variabl…
The WHO-5 Well-Being Index – Validation based on item response theory and the analysis of measurement invariance across 35 countries.
2020
Abstract Background The five-item World Health Organization Well-Being Index (WHO-5) is a frequently used brief standard measure in large-scale cross-cultural clinical studies. Despite its frequent use, some psychometric questions remain that concern the choice of an adequate item response theory (IRT) model, the evaluation of reliability at important cutoff points, and most importantly the assessment of measurement invariance across countries. Methods Data from the 6th European Working Condition survey (2015) were used that collected nationally representative samples of employed and self-employed individuals (N = 43,469) via computer-aided personal interviews across 35 European countries. …
Subjective well-being key elements of Successful Aging: A study with Lifelong Learners older adults from Costa Rica and Spain.
2019
Abstract Subjective well-being is a major psychological construct in the research tradition. Along with literature, authors have distinguished between hedonic and eudaimonic well-being. The aim of this study is to determine the role of some psychosocial variables plays in the perceived well-being is conceived from a hedonic or a eudaimonic perspective. The sample consisted of 1016 people of 55 years and older in a Spanish sample and 277 people of 55 years old or older from a Costa Rican sample. Both samples were part of the Longitudinal Older Learners (LOL) study. A structural model with latent variables was estimated with Mplus. The results point out that, the traditional variables include…
Advances in blind source separation for spatial data
2021
Viele Datensaetze bestehen aus multivariaten Messungen, die an verschiedenen geographischen Orten durchgefuehrt wurden. Typischerweise besitzen solche Datensaetze die Eigenschaft, dass Messungen in unmittelbarer Naehe aehnlicher sind als Messungen, die eine hohe Entfernung aufweisen. In der statistischen Analyse solcher raeumlichen Daten sollte diese spezielle Eigenschaft beruecksichtigt werden. In letzter Zeit wurde in der statistischen Literatur die sogenannte Blind Source Separation Methode auf raeumliche Daten erweitert. In diesem Model wird angenommen, dass die Daten aus Linearkombinationen von unbeobachteten Variablen bestehen, und das Ziel ist diese latenten Variablen zu bestimmen. D…
Impact of missing data mechanism on the estimate of change: a case study on cognitive function and polypharmacy among older persons
2015
Piia Lavikainen,1,2 Esko Leskinen,3 Sirpa Hartikainen,1,2 Jyrki Möttönen,4 Raimo Sulkava,5 Maarit J Korhonen6 1Kuopio Research Centre of Geriatric Care, University of Eastern Finland, Kuopio, Finland; 2School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland; 3Department of Mathematics and Statistics, University of Jyväskylä, Jyväskylä, Finland; 4Department of Social Research, University of Helsinki, Helsinki, Finland; 5Department of Geriatrics, Institute of Public Health and Clinical Nutrition, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland; 6Department of Pharmacology, D…
Fast and universal estimation of latent variable models using extended variational approximations
2022
AbstractGeneralized linear latent variable models (GLLVMs) are a class of methods for analyzing multi-response data which has gained considerable popularity in recent years, e.g., in the analysis of multivariate abundance data in ecology. One of the main features of GLLVMs is their capacity to handle a variety of responses types, such as (overdispersed) counts, binomial and (semi-)continuous responses, and proportions data. On the other hand, the inclusion of unobserved latent variables poses a major computational challenge, as the resulting marginal likelihood function involves an intractable integral for non-normally distributed responses. This has spurred research into a number of approx…
Blind source separation for non-stationary random fields
2022
Regional data analysis is concerned with the analysis and modeling of measurements that are spatially separated by specifically accounting for typical features of such data. Namely, measurements in close proximity tend to be more similar than the ones further separated. This might hold also true for cross-dependencies when multivariate spatial data is considered. Often, scientists are interested in linear transformations of such data which are easy to interpret and might be used as dimension reduction. Recently, for that purpose spatial blind source separation (SBSS) was introduced which assumes that the observed data are formed by a linear mixture of uncorrelated, weakly stationary random …