Dataset Information

Composition or Context: Using Transportability to Understand Drivers of Site Differences in a Large-scale Housing Experiment.

ABSTRACT: BACKGROUND:The Moving To Opportunity (MTO) experiment manipulated neighborhood context by randomly assigning housing vouchers to volunteers living in public housing to use to move to lower poverty neighborhoods in five US cities. This random assignment overcomes confounding limitations that challenge other neighborhood studies. However, differences in MTO's effects across the five cities have been largely ignored. Such differences could be due to population composition (e.g., differences in the racial/ethnic distribution) or to context (e.g., differences in the economy). METHODS:Using a nonparametric omnibus test and a multiply robust, semiparametric estimator for transportability, we assessed the extent to which differences in individual-level compositional characteristics that may act as effect modifiers can account for differences in MTO's effects across sites. We examined MTO's effects on marijuana use, behavioral problems, major depressive disorder, and generalized anxiety disorder among black and Latino adolescent males, where housing voucher receipt was harmful for health in some sites but beneficial in others. RESULTS:Comparing point estimates, differences in composition partially explained site differences in MTO effects on marijuana use and behavioral problems but did not explain site differences for major depressive disorder or generalized anxiety disorder. CONCLUSIONS:Our findings provide quantitative, rigorous evidence for the importance of context or unmeasured individual-level compositional variables in modifying MTO's effects.

SUBMITTER: Rudolph KE

PROVIDER: S-EPMC5792307 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Composition or Context: Using Transportability to Understand Drivers of Site Differences in a Large-scale Housing Experiment.

Rudolph Kara E KE Schmidt Nicole M NM Glymour M Maria MM Crowder Rebecca R Galin Jessica J Ahern Jennifer J Osypuk Theresa L TL

Epidemiology (Cambridge, Mass.) 20180301 2

<h4>Background</h4>The Moving To Opportunity (MTO) experiment manipulated neighborhood context by randomly assigning housing vouchers to volunteers living in public housing to use to move to lower poverty neighborhoods in five US cities. This random assignment overcomes confounding limitations that challenge other neighborhood studies. However, differences in MTO's effects across the five cities have been largely ignored. Such differences could be due to population composition (e.g., differences ...[more]

PMID: 29076878

Similar Datasets

Project description:A better understanding of deforestation drivers across countries and spatial scales is a precondition for designing efficient international policies and coherent land use planning strategies such as REDD+. However, it is so far unclear if the well-studied drivers of tropical deforestation behave similarly across nested subnational jurisdictions, which is crucial for efficient policy implementation. We selected three countries in Africa, America and Asia, which present very different tropical contexts. Making use of spatial econometrics and a multi-level approach, we conducted a set of regressions comprising 3,035 administrative units from the three countries at micro-level, plus 361 and 49 at meso- and macro-level, respectively. We included forest cover as dependent variable and seven physio-geographic and socioeconomic indicators of well-known drivers of deforestation as explanatory variables. With this, we could provide a first set of highly significant econometric models of pantropical deforestation that consider subnational units. We identified recurrent drivers across countries and scales, namely population pressure and the natural condition of land suitability for crop production. The impacts of demography on forest cover were strikingly strong across contexts, suggesting clear limitations of sectoral policy. Our findings also revealed scale and context dependencies, such as an increased heterogeneity at local scopes, with a higher and more diverse number of significant determinants of forest cover. Additionally, we detected stronger spatial interactions at smaller levels, providing empirical evidence that certain deforestation forces occur independently of the existing de jure governance boundaries. We demonstrated that neglecting spatial dependencies in this type of studies can lead to several misinterpretations. We therefore advocate, that the design and enforcement of policy instruments-such as REDD+-should start from common international entry points that ensure for coherent agricultural and demographic policies. In order to achieve a long-term impact on the ground, these policies need to have enough flexibility to be modified and adapted to specific national, regional or local conditions.

Project description:BackgroundNut-bearing trees, including oaks (Quercus spp.), are considered to be highly dispersal limited, leading to concerns about their ability to colonize new sites or migrate in response to climate change. However, estimating seed dispersal is challenging in species that are secondarily dispersed by animals, and differences in disperser abundance or behavior could lead to large spatio-temporal variation in dispersal ability. Parentage and dispersal analyses combining genetic and ecological data provide accurate estimates of current dispersal, while spatial genetic structure (SGS) can shed light on past patterns of dispersal and establishment.Methodology and principal findingsIn this study, we estimate seed and pollen dispersal and parentage for two mixed-species red oak populations using a hierarchical bayesian approach. We compare these results to those of a genetic ML parentage model. We also test whether observed patterns of SGS in three size cohorts are consistent with known site history and current dispersal patterns. We find that, while pollen dispersal is extensive at both sites, the scale of seed dispersal differs substantially. Parentage results differ between models due to additional data included in bayesian model and differing genotyping error assumptions, but both indicate between-site dispersal differences. Patterns of SGS in large adults, small adults, and seedlings are consistent with known site history (farmed vs. selectively harvested), and with long-term differences in seed dispersal. This difference is consistent with predator/disperser satiation due to higher acorn production at the low-dispersal site. While this site-to-site variation results in substantial differences in asymptotic spread rates, dispersal for both sites is substantially lower than required to track latitudinal temperature shifts.ConclusionsAnimal-dispersed trees can exhibit considerable spatial variation in seed dispersal, although patterns may be surprisingly constant over time. However, even under favorable conditions, migration in heavy-seeded species is likely to lag contemporary climate change.

Dataset Information

Composition or Context: Using Transportability to Understand Drivers of Site Differences in a Large-scale Housing Experiment.

Publications

Composition or Context: Using Transportability to Understand Drivers of Site Differences in a Large-scale Housing Experiment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure