Selection Effects Research Articles

Partners' health and silver splits in Europe: A gendered pattern?

AbstractObjectiveBuilding on the Theory of Dyadic Illness Management, this paper addresses the correlates of silver splits—voluntary union dissolutions after age 50—among mixed‐gender couples in Europe focusing on the role of partners' health status.BackgroundFamily diversity at older ages is growing in wealthy countries, with late union dissolutions increasingly occurring through separation and divorce rather than widowhood. Nonetheless, the correlates of silver splits in Europe, particularly regarding health within couples, remain underexplored.MethodWe utilized data from the European Survey of Health, Ageing, and Retirement (SHARE), spanning Waves 1 (2004–2005) to 9 (2021–2022), and employed discrete‐time event‐history analysis to model the risk of silver splits, separately among couples aged 50–64 and 65+ (N = 31,915 and 48,361 couple‐years, respectively). We inspected three health dimensions: self‐rated health, Global Activity Limitations Index, depression.ResultsWe found a non‐negligible and gendered association between health and union dissolution among couples aged 50–64. Couples in which the woman reported poor self‐rated health or faced severe activity limitations, whereas the man maintained good health, exhibited a higher risk of silver splits compared to couples in good health. Conversely, the risk of silver splits did not change significantly when the man experienced poor self‐rated health or activity limitations compared to couples in good health. Results among older couples suggested that the health/silver split link weakens with age.ConclusionGendered health‐related selection effects appear among older European couples, as men struggle more than women with a partner's declining health, potentially jeopardizing the couple's stability.

Image dataset: UAV images and ground data of one 'Bingo' mandarin and two 'Valencia' orange rootstock trials conducted in Florida.

The data are aerial images and ground tree measurement data of 3 citrus rootstock trials. Developing new citrus rootstock varieties requires field trials to test to identify selections with improved horticultural performance. A bud from a scion variety is grafted onto the rootstock and grown in a nursery until the grafted plant is ready to be planted in the field, which is in about one year. Trees in the field are assessed each year by measuring height, canopy diameter in 2 dimensions, overall health, and fruit number and quality factors when the trees begin to have a significant crop (∼3 years). Data collection of each tree is done manually. The image and ground data sets are of 3 rootstock trials that includes a 3-year-old Bingo mandarin hybrid trial of 206 trees, a 6-year-old Valencia orange trial of 643 trees, and a 7-year-old Valencia orange trials of 648 trees. Data for each trial includes aerial images and ground data of height, canopy diameters, and an overall health rating. The combination of ground validated measures and aerial images make this data set useful for building AI-based aerial image data collection applications. The data will be useful for 1) visualizing the effects of different rootstock selections and varieties on scion growth, effects that may not be fully captured with single measure metrics; and 2) development of image analysis applications and segmentation algorithms that can extract data from the images that are suitable for replacing some or all the ground measures.

Inferring demographic and selective histories from population genomic data using a two-step approach in species with coding-sparse genomes: an application to human data.

The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.

Research on LD-pumped single-frequency laser based on twisted-mode-cavity and RVBG

Abstract Single-frequency lasers have the advantages of good spectral purity, high peak spectral density, long coherence distance and low phase noise. They are widely used in fields such as laser spectroscopy, laser lidar, sodium guide stars, coherent optical communication and high-resolution measurement. We designed an all-solid-state single-frequency laser based on twisted-mode-cavity (TMC) structure and used a reflective volume Bragg grating (RVBG) to replace the ordinary output mirror. Through the composite mode selection effect of the twisted-mode-cavity and RVBG, the occurrence of multi-longitudinal mode oscillation is eliminated successfully, and precise optical frequency selection is achieved. When the pump power reached 88.0 W, the output power was 1.6 W, allowing for stable single-frequency laser operation at 1064.44 nm, with an output laser linewidth of 9.77 × 10−3 pm, the corresponding slope efficiency was 10.00%, and the light-to-light conversion efficiency was 1.82%. The power instability was less than 4.44% and the beam quality factor were M x 2 = 1.35 , M y 2 = 1.38 . Experimental results show that compared with using a RVBG or twisted-mode-cavity individually, the combination of the two methods can significantly compress the laser linewidth and achieve single-frequency laser output.

Do Competitive Markets Clean Up the US Electricity Sector?: Evidence From the Southwest Power Pool

In the US, there has been a movement toward competitive electricity markets with system-operator auctions. However, the impact of such market reforms on non-market outcomes like emission rates remains unclear. We decompose how competition in wholesale electricity markets can affect carbon emission rates of electricity generating units (EGUs) through process, reallocation, and selection effects. Using event-study and difference-indifference strategies, we quantify the Day-Ahead Market’s (DAM) environmental impact in the Southwest Power Pool and assess the importance of each channel, with Pennsylvania, New Jersey, and Maryland interconnection serving as the comparison group. We find DAM reduced average carbon emission rates of EGUs by 0.033 tons per MWh, a roughly 4 percent reduction. This reduction is primarily driven by the selection effect: emission-intensive and uneconomical EGUs retire after the DAM market reform. This corresponds to an annual avoidance of 7.66 million tons of carbon dioxide emissions, worth approximately $383.4 million in avoided damages. JEL Classification: L51, L94, Q48, Q53

Selection effects in the births of mutual funds

AbstractNewborn funds disproportionately hold popular stocks, representing long‐lived strategic choices. This suggests that when choosing strategies in which to launch new funds, families do not consider only expectations for their own performance but also consider investor sentiment toward those strategies. The two motives for entry result in an interaction effect between competitive entry and strategy popularity, which affects performance and flows for both existing and newborn funds. Newborn funds' expectations for performance are partly driven by fund manager skill in those strategies, but this is not the only factor, leaving a role for time‐varying investment opportunities.

No road with roses in developing countries: gender diversification in firm leadership and total factor productivity

Abstract The paper investigates the gender-driven disparities in total factor productivity (TFP) between women-owned enterprises (WOEs) and male-owned enterprises (MOEs) across 30 developing countries. Utilizing firm-level data from the World Bank Enterprise Surveys, the study addresses biases in previous gender literature by employing a semi-parametric technique to more accurately measure TFP. The results reveal a significant TFP gap, with WOEs being 5.5% to 6.7% less productive than MOEs, even after controlling for key firm characteristics like age, innovation, human capital, and ownership status. The study attributes this productivity disparity primarily to financial obstacles faced by WOEs, which hinder their ability to innovate and capitalize on opportunities. The lack of access to credit leads to a misallocation of capital, excluding equally efficient women entrepreneurs from financial resources that could stimulate productivity. Contrary to some assumptions, the study finds no evidence that WOEs underperform in sectors with high financial dependence, suggesting that WOEs are not inherently inefficient in their use of capital. Our findings provide causal evidence as we control for selectivity bias in the TFP-WOEs nexus by identifying exogenously the factors that affect financial constraints and innovation.

Joint Modelling of Astrophysical Systematics for Cosmology with LSST Cosmic Shear

Abstract We present a novel framework for jointly modelling the weak lensing source galaxy redshift distribution and the intrinsic alignment (IA) of galaxies through a shared luminosity function (LF). In the context of a Rubin Observatory’s Legacy Survey of Space and Time (LSST) Year 1 and Year 10 cosmic shear analysis, we show that our novel approach produces cosmological parameter constraints which are comparable to standard methods, while offering more physical insight into IA and selection effects. We clarify the relationship between individual parameters of a Schechter luminosity function and the redshift distribution of a magnitude-limited sample, showing the consequences of marginalizing over these parameters when modelling intrinsic alignments in standard cosmic shear analyses. We explore the impact of the shape of the luminosity function on the cosmic shear data vector, and we outline the potential of this method to naturally model selection functions in redshift distribution estimation. Although this work focuses on LSST cosmic shear, the proposed joint modelling framework is broadly applicable to weak lensing surveys.

KiDS-Legacy: Angular galaxy clustering from deep surveys with complex selection effects

Photometric galaxy surveys, despite their limited resolution along the line of sight, encode rich information about the large-scale structure (LSS) of the Universe thanks to the high number density and extensive depth of the data. However, the complicated selection effects in wide and deep surveys can potentially cause significant bias in the angular two-point correlation function (2PCF) measured from those surveys. In this paper, we measure the 2PCF from the newly published KiDS-Legacy sample. Given an r-band $5σ$ magnitude limit of $24.8$ and survey footprint of $1347$ deg^2, it achieves an excellent combination of sky coverage and depth for such a measurement. We find that complex selection effects, primarily induced by varying seeing, introduce over-estimation of the 2PCF by approximately an order of magnitude. To correct for such effects, we apply a machine learning-based method to recover an organised random (OR) that presents the same selection pattern as the galaxy sample. The basic idea is to find the selection-induced clustering of galaxies using a combination of self-organising maps (SOMs) and hierarchical clustering (HC). This unsupervised machine learning method is able to recover complicated selection effects without specifying their functional forms. We validate this SOM+HC method on mock deep galaxy samples with realistic systematics and selections derived from the KiDS-Legacy catalogue. Using mock data, we demonstrate that the OR delivers unbiased 2PCF cosmological parameter constraints, removing the $27σ$ offset in the galaxy bias parameter that is recovered when adopting uniform randoms. Blinded measurements on the real KiDS-Legacy data show that the corrected 2PCF is robust to the SOM+HC configuration near the optimal set-up suggested by the mock tests.

DOP013 Risk of immune mediated inflammatory diseases associated with anti-TNFs and ustekinumab in Crohn’s disease: a nationwide population-based cohort study

Abstract Background Biologics have been variously associated with an increased risk of paradoxical immune mediated inflammatory diseases (IMIDs) in patients with Crohn’s disease (CD). While this risk has been assessed in cohort studies for tumor necrosis factor inhibitors (anti-TNF), only case reports have reported the paradoxical occurrence of IMIDs in patients treated with ustekinumab. The aim of this study was to assess the risk of an incident second IMID in patients with CD treated with anti-TNF and ustekinumab. Methods We identified individuals with CD and no other IMIDs switching after a first anti-TNF to either a second anti-TNF or ustekinumab based on the French administrative healthcare databases 2008-2022. The primary outcome was the occurrence of a second IMID, including inflammatory rheumatic diseases (rheumatoid arthritis, ankylosing spondylitis, psoriatic arthritis, and polymyalgia rheumatica), skin diseases (psoriasis, hidradenitis suppurativa, and vitiligo), neurologic diseases (multiple sclerosis, myasthenia gravis), thyroiditis, connective tissue diseases, and vasculitis. Follow-up started from treatment switch until occurrence of a second IMID, treatment withdrawal, or December 31, 2022. A lag period of 3 months was considered to minimize protopathic bias. Hazard ratios for the risk of second IMID were calculated, following 1:1 propensity score (PS) weighting, in order to control for confounders including demographics, previous and baseline IBD disease activity, co-treatment exposure, and comorbidities. Results Among 13,994 CD patients included, 10,712 (76.5%) and 3,282 (23.5%) patients were exposed to a second anti-TNF and ustekinumab, respectively. The overall proportion of women was 59.6%. Mean age at cohort entry was 38.0 (SD, 13.8) and 41.6 years (SD, 14.8) in the anti-TNF and ustekinumab groups, respectively. The median follow-up was 5.7 years (IQR, 3.3-9.1). Overall, 578 incident second IMID occurred (incidence rates: 23.2 per 1000 PY, person-years), mainly consisting in psoriasis (350, 60.6%) and ankylosing spondylitis (117, 20.2%). The cumulative incidence of second IMID after 10 years of follow-up was 9.85% (confidence interval 95% [8.84-10.85]). All covariates included in the PS model were balanced with an absolute standardized difference lower than 0.1. The risk of second IMID was lower in patients exposed to ustekinumab compared to those exposed to a second anti-TNF (HR=0.63 CI 95%[0.48-0.81], p-value<0.001). Conclusion Based on a population-based and propensity score weighted cohort of 13,994 CD patients, exposure to ustekinumab was associated with a lower risk of second IMID compared to anti-TNF.

Measuring social integration, treatment, and mortality after substance use treatment: methodological elaborations in a 20-year follow-up study

ObjectiveAlcohol and Other Drug (AOD) disorders cause substantial harm. Effective Substance Use Treatment (SUT) exists, but long-term outcomes remain inconclusive. This study used a 20-year prospective follow-up of 1248 service users entering SUT in Stockholm, Sweden, in 2000–2002 to elaborate on how different dimensions of long-term outcomes may be measured by register-based indicators. Baseline characteristics and attrition bias were explicated, and register-based outcomes were examined.ResultsRegister-based indicators are valuable, but they also have inherent limitations such as the lack of substance use data and inability to differentiate between un/met treatment needs and access. Significant variations in long-term outcomes were evident depending on which register-based indicator was used, and whether used in isolation or combinations. Six out of 10 service users were still alive after 20 years, but as many as 8 out of 10 of the survivors remained in treatment, and only two out of 10 had a stable economic situation. Hence, the register indicators identified only a few survivors, with stable economic and social situations, and without recent treatment contacts 20 years after treatment entry. The long-term outcomes were concerning and even more so when combining outcome dimensions.

Trade Induced Selection Effects: Factor Intensity Difference in Entry and Production Costs

Trade Induced Selection Effects: Factor Intensity Difference in Entry and Production Costs

Using internet-assisted geocoding of 1940 census addresses to reconstruct enumeration districts for use with redlining and longitudinal health datasets.

Many historical administrative documents, such as the 1940 census, have been digitized and thus could be merged with geographic data. Merged data could reveal social determinants of health, health and social policy milieu, life course events, and selection effects otherwise masked in longitudinal datasets. However, most exact boundaries of 1940 census enumeration districts have not yet been georeferenced. These exact boundaries could aid in analysis of redlining and other geographic and social contextual factors important for health outcomes today. Our objective is to locate and map a large set of 1940 enumeration districts. We use online resources and algorithmic solutions to locate and georeference unknown 1940 enumeration districts. We geocode addresses using the OpenCage API and construct "virtual" enumeration districts by using a convex hull algorithm on those geocoded addresses. We also merge in Home Owners' Loan Corporation (HOLC) redlining maps from the 1930s to demonstrate how 1940 enumeration districts could be used in future work to examine the association between historic redlining and current health. We geocode 7,228,656 1940 census addresses from the largest 191 US cities in 1940 that contained 84% of the 1940 US urban population from the Geographic Reference File and construct 34,472 virtual enumeration districts in areas that had HOLC redlining maps. 18,340 virtual enumeration districts were previously unmapped, covering cities containing an additional 40% of the 1940 US urban population. Where virtual enumeration districts match with previously mapped districts, 96.8% of paired districts share HOLC redlining categorization. Researchers can use algorithmic methods to quickly process, geocode, merge, and analyze large scale repositories of historical documents that provide important data on social determinants of health. These 1940 enumeration district maps could be used with studies such as the Health and Retirement Study, Panel Study for Income Dynamics, and Wisconsin Longitudinal Study.

Loan selection, attribute substitution and information effect

PurposeBorrowers are usually presented with a menu of similar-looking options when selecting a loan plan. However, it remains unclear whether they are able to choose the most cost-effective plan. This study aims to investigate whether people select loan plans optimally, whether their choices are influenced by the informational cues provided to them and how their selections change with the provision of additional loan-related information.Design/methodology/approachThe study uses a within-participant experimental design, where participants are presented with similar-looking loan plans but with different present discounted costs. Subjects are asked to rank those plans, with the minimum present discounted cost plan maximizing their experimental payoff. The loan plans across different rounds are presented with different informational cues to see whether that influences participants' ability to select the cost-minimizing loan plans.FindingsThe author finds that participants were 78% likely to state a suboptimal preference ordering and 68% likely to select a loan plan that does not minimize cost. There is suggestive evidence regarding the role of attribute substitution in the decision-making process, wherein participants substituted annual percentage rate (APR) and total cost attributes for the present discounted cost of a loan plan. Additionally, the author presents causal evidence demonstrating how providing additional information can influence the choice of the substituted attribute.Originality/valueResearch has indicated that individuals often make suboptimal financial decisions, particularly in complex decision contexts. Examples include selecting medical insurance, a retirement savings plan, a student loan or borrowing on a credit card. This paper demonstrates that similar biases are present when individuals borrow using a loan plan, wherein they tend to substitute the APR or total cost of the loan plan for the present discounted cost of the loan plan. Furthermore, the study reveals that the impact of providing more information to borrowers can vary, depending on the combination of loan plans being considered.

Near-IR clumps and their properties in high-z galaxies with JWST/NIRCam

ABSTRACT Resolved stellar morphology of $z\gt 1$ galaxies was inaccessible before JWST. This limitation, due to the impact of dust on rest-frame UV light, had withheld major observational conclusions required to understand the importance of clumps in galaxy evolution. Essentially independent of this issue, we use the rest-frame near-IR for a stellar-mass dependent clump detection method and determine reliable estimations of selection effects. We exploit publicly available JWST/NIRCam and HST/ACS imaging data from CEERS, to create a stellar-mass based picture of clumps in a mass-complete sample of 418 galaxies within a wide wavelength coverage of $0.5{\!-\!}4.6\, \mu$m and a redshift window of $1 \lt z \lt 2$. We find that a near-IR detection gives access to a larger, and possibly different, set of clumps within galaxies, with those also detected in UV making up only 28 per cent. Whereas, 85 per cent of the UV clumps are found to have a near-IR counterpart. These near-IR clumps closely follow the UVJ classification of their respective host galaxies, with these hosts mainly populating the star-forming regime besides a fraction of them (16 per cent) that can be considered quiescent. The mass of the detected clumps are found to be within the range of $10^{7.5{\!-\!}9.5}\, \rm {\rm M}_{\odot }$, therefore expected to drive gas into galaxy cores through tidal torques. The clump stellar mass function is found to have a slope of $-1.50 \pm 0.14$, indicating a hierarchical nature similar to that of star-forming regions in the local Universe. Finally, we observe a radial gradient of increasing clump mass towards the centre of galaxies.

Meta-analysis reveals global variations in plant diversity effects on productivity.

Positive effects of plant diversity on productivity have been globally demonstrated and explained by two main effects: complementarity effects and selection effects1-4. However, plant diversity experiments have shown substantial variation in these effects, with driving factors poorly understood4-6. On the basis of a meta-analysis of 452 experiments across the globe, we show that productivity increases on average by 15.2% from monocultures to species mixtures with an average species richness of 2.6; net biodiversity effects are stronger in grassland and forest experiments and weaker in container, cropland and aquatic ecosystems. Of the net biodiversity effects, complementarity effects and selection effects contribute 65.6% and 34.4%, respectively. Complementarity effects increase with phylogenetic diversity, the mixing of nitrogen-fixing and non-nitrogen-fixing species and the functional diversity of leaf nitrogen contents, which indicate the key roles of niche partitioning, biotic feedback and abiotic facilitation in complementarity effects. More positive selection effects occur with higher species biomass inequality in their monocultures. Complementarity effects increase over time, whereas selection effects decrease over time, and they remain consistent across global variations in climates. Our results provide key insights into understanding global variations in plant diversity effects on productivity and underscore the importance of integrating both complementarity and selection effects into strategies for biodiversity conservation and ecological restoration.

Genomic prediction accounting for dominance and epistatic genetic effects on litter size traits in Large White pigs.

Litter size traits of sows are crucial for the economic benefits of the pig industry. Three phenotypic traits of 1,206 Large White (LW) pigs, that is, the total number born (TNB), number born alive (NBA), and number of healthy piglets (NHP), were recorded. We evaluated a series of genomic best linear unbiased prediction (GBLUP) models that sequentially added additive effects (model A), dominance effects (model A+D), and epistatic effects (model A+D+AA, model A+D+AA+AD, and model A+D+AA+AD+DD) using chip data and imputed whole-genome sequencing (WGS) data to estimate genetic parameters and predictive accuracy. The reproductive traits of sows showed low heritability in this study, with narrow heritability of the three traits ranging from 0.030 to 0.064, and broad heritability ranging from 0.125 to 0.145. The inclusion of non-additive effects in the model improved the accuracy of genomic selection. In the chip data, compared with that of the A model, the A+D+AA+AD+DD model showed the greatest increase in accuracy for TNB, NBA, and NHP, with improvements of 1.78, 1.67, and 1.74%, respectively. Additionally, the accuracy of the imputed WGS data was greater compared to the chip data. For the TNB, NBA, and NHP traits, the predictive accuracy of the imputed WGS data improved by 3.26, 7.72, and 3.00%, respectively, compared with that of the chip data. In summary, these results suggest that non-additive effects in genomic selection could improve prediction accuracy and should be considered in pig genomic evaluation procedures.

Effectiveness of oral health promotion in children and adolescents through behaviour change interventions: A scoping review.

To explore the interventions for change in oral health behaviour that are effective in improving oral health behaviours in 8 to 18-year-old children during oral health promotion. The Joanna Briggs Institute framework of evidence synthesis for conducting a scoping review was implemented for the methodology. Included studies related to the objective, measured clinical or non-clinical outcomes, were in English, 2011-2023, and were experimental, observational or reviews. PUBMED, Science-Direct, Scopus and Sabinet were systematically searched with predetermined search strings. Studies were selected by appraisal of the title, abstract and full text. Data were extracted using a standardised template and the key questions were addressed via a qualitative analysis. Searches yielded 407 articles from electronic databases. Of these, 290 articles were excluded, and 47 full-text studies were assessed for eligibility, with 23 studies and two systematic reviews finalised for inclusion. In addition, a PEARL search was conducted from the reference lists of other studies. Most studies (91.3%) focused on educating children directly; 8.7% indirectly influenced parents, guardians, and teachers. Interventions focused largely on traditional oral health education presented in diverse forms and via different platforms. Studies differentiated clinical outcomes (indices) from non-clinical outcomes (knowledge, behaviour). All included RCTs were of different quality regarding selection, performance and detection bias. But all studies indicated a low risk of bias in attrition and Reporting bias. Seventeen of the 25 studies (68%) were not based on any behaviour change theory. Oral health interventions based on motivational interviewing and the social cognitive theory have been shown to be to be effective. Interventions could also include practical tooth brushing activities, gamification, audio-visual components, as well as reinforcement and repetition in the longer term. Future oral health promotion in children should be designed to include these elements. There is a need for higher quality studies in this field, with future research being urged to provide detailed intervention descriptions and incorporate longer follow-up periods.

Understanding the Selection Effect of WFH: Evidence from Survey Data

Understanding the Selection Effect of WFH: Evidence from Survey Data

TMS-induced modulation of brain networks and its associations to rTMS treatment for depression: a concurrent fMRI-EEG-TMS study.

Transcranial magnetic stimulation (TMS) over the left dorsolateral prefrontal cortex (L-DLPFC) is an established intervention for treatment-resistant depression (TRD), yet the underlying therapeutic mechanisms remain not fully understood. This study employs an integrative approach that combines TMS with concurrent functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), aimed at assessing the acute/immediate effects of TMS on brain network dynamics and their correlation with clinical outcomes. Our study demonstrates that TMS acutely modulates connectivity within vital brain circuits, particularly the cognitive control and default mode networks. We found that the baseline TMS-evoked responses in the cognitive control and limbic networks significantly predicted clinical improvement in patients receiving a novel EEG-synchronized repetitive TMS treatment. Furthermore, this study explored the brain-state dependent effects of TMS, as the brain-state indexed by the phase of EEG prefrontal alpha oscillation. We found that clinical outcomes in this novel treatment are linked to state-specific TMS-modulated functional connectivity within a pivotal brain circuit of the L-DLPFC and the posterior subgenual anterior cingulate cortex within the limbic system. These findings contribute to our understanding of the therapeutic effects underlying TMS treatment in depression and support the potential of assessing state-dependent TMS effects in TMS timing target selection. This study emphasizes the importance of personalized timing of TMS for optimizing target engagement of specific clinically relevant brain circuits. Our results are crucial for future research into the development of personalized neuromodulation therapies for TRD patients.