Underlying Sources Of Variation Research Articles

A Dynamic Spatial Factor Model to Describe the Opioid Syndemic in Ohio.

The opioid epidemic has been ongoing for over 20 years in the United States. As opioid misuse has shifted increasingly toward injection of illicitly produced opioids, it has been associated with HIV and hepatitis C transmission. These epidemics interact to form the opioid syndemic. We obtain annual county-level counts of opioid overdose deaths, treatment admissions for opioid misuse, and newly diagnosed cases of acute and chronic hepatitis C and newly diagnosed HIV from 2014 to 2019. Aligned with the conceptual framework of syndemics, we develop a dynamic spatial factor model to describe the opioid syndemic for counties in Ohio and estimate the complex synergies between each of the epidemics. We estimate three latent factors characterizing variation of the syndemic across space and time. The first factor reflects overall burden and is greatest in southern Ohio. The second factor describes harms and is greatest in urban counties. The third factor highlights counties with higher than expected hepatitis C rates and lower than expected HIV rates, which suggests elevated localized risk for future HIV outbreaks. Through the estimation of dynamic spatial factors, we are able to estimate the complex dependencies and characterize the synergy across outcomes that underlie the syndemic. The latent factors summarize shared variation across multiple spatial time series and provide new insights into the relationships between the epidemics within the syndemic. Our framework provides a coherent approach for synthesizing complex interactions and estimating underlying sources of variation that can be applied to other syndemics.

Genetic and Environmental Causes of Individual Differences in Daily Life Positive Affect and Reward Experience and Its Overlap with Stress-Sensitivity

Momentary positive affect (PA) and reward experience may underlie subjective wellbeing, and index mental health resilience. This study examines their underlying sources of variation and the covariation with stress-sensitivity. The experience sampling method was used to collect multiple appraisals of mood and daily life events in 520 female twins. Structural equation model fitting was employed to determine sources of variation of PA, reward experience, and the association between reward experience and stress-sensitivity. PA was best explained by shared and non-shared environmental factors, and reward experience by non-shared environmental factors only, although the evidence was also suggestive of a small genetic contribution. Reward experience and stress-sensitivity showed no association. PA was not heritable. Most-if not all-variance of reward experience was explained by environmental influences. Stress-sensitivity, indexing depression vulnerability, and reward experience were non-overlapping, suggesting that resilience traits are independent from stress-sensitivity levels in a general population sample.

Reconciling Scattered Images

Any organizational environment is filled with many different types of organizational images, some sent by a focal organization, some sent by outside arbiters, and others formed by interested stakeholders. As organizations attempt to communicate directly to segmented audiences by using tailored images, they also indirectly, and sometimes unwittingly, create a broader array of images of themselves. The resulting spectrum of images cumulates into a scattered images problem. That is, the many sent images (expressions) and received images (impressions) constitute a collection of potentially disparate organizational images that need to be reconciled. The authors explore this increasingly troublesome scattered images problem; the authors also propose a taxonomy of images and discuss their underlying sources of variation. Finally, the authors discuss why and how some organizations are able to mitigate the scattered images problem, arguing that organizational complexity, visibility, and image equivocality will influence an organization's ability to better control its own image.

Population estimation with sparse data: the role of estimators versus indices revisited

The use of indices to evaluate small-mammal populations has been heavily criticized, yet a review of small-mammal studies published from 1996 through 2000 indicated that indices are still the primary methods employed for measuring populations. The literature review also found that 98% of the samples collected in these studies were too small for reliable selection among population-estimation models. Researchers therefore generally have a choice between using a default estimator or an index, a choice for which the consequences have not been critically evaluated. We examined the use of a closed-population enumeration index, the number of unique individuals captured (Mt+1), and 3 population estimators for estimating simulated small populations (N = 50) under variable effects of time, trap-induced behavior, individual heterogeneity in trapping probabilities, and detection probabilities. Simulation results indicated that the estimators produced population estimates with low bias and high precision when the estimator reflected the underlying sources of variation in capture probability. However, when the underlying sources of variation deviated from model assumptions, bias was often high and results were inconsistent. In our simulations, Mt+1 generally exhibited lower variance and less sensitivity to the sources of variation in capture probabilities than the estimators.

Het ontstaan van een frequentieverdeling*

SummaryThe genesis of frequency distributionsThe next set of six short papers reproduces the contents of a series of six talks given at the annual meeting of the ‘Vereniging voor Statistiek’ (Statistical Society) having ‘frequency distributions’ for their subject.In this first and introductory paper the various ways in wich we may conceive a frequency distributions to be generated aye briefly indicated, and the useful conclusions with regard to the underlying sources of variation that may often be drawn from the shape of an observed frequency distribution are pointed out.