LAUSR

About LAUSR
Donate
Contact Us

Follow us:

You are not signed in:

Sign Up!


   Articles with "sampling bias" as a keyword



Representativeness of autistic samples in studies recruiting through social media

Sign Up to like & get
recommendations! Published in 2022 at "Autism Research"

DOI: 10.1002/aur.2777

Abstract: Survey‐based research with recruitment through online channels is a convenient way to obtain large samples and has recently been increasingly used in autism research. However, sampling from online channels may be associated with a high… read more here.

Keywords: representativeness autistic; social media; autism; autistic samples ... See more keywords

Integrating multiple data sources and multi-scale land-cover data to model the distribution of a declining amphibian

Sign Up to like & get
recommendations! Published in 2020 at "Biological Conservation"

DOI: 10.1016/j.biocon.2019.108374

Abstract: Abstract Determining the spatial scale at which landscape features influence population persistence is an important task for conservation planning. One challenge is that sampling biases confound factors that influence species occurrence and survey effort. Recent… read more here.

Keywords: cover data; sampling bias; model distribution; western spadefoots ... See more keywords

Accounting for the last-sampling bias in perceptual decision-making

Sign Up to like & get
recommendations! Published in 2022 at "Cognition"

DOI: 10.1016/j.cognition.2022.105049

Abstract: Human decisions are replete with biases that often reflect the underlying mechanisms of the decision-making process. The current study focused on a bias observed in different modalities and decision domains; the last-sampling bias, whereby people… read more here.

Keywords: perceptual decision; last sampling; decision; decision making ... See more keywords

Sampling biases and mitigations in modeling shale reservoirs

Sign Up to like & get
recommendations! Published in 2019 at "Journal of Natural Gas Science and Engineering"

DOI: 10.1016/j.jngse.2019.102968

Abstract: Abstract Field development of a shale reservoir is different from developing conventional reservoirs because of the tightness of formations and extensive use of horizontal wells. One critical consequence of horizontal wells is the sampling bias.… read more here.

Keywords: horizontal wells; reservoir; sampling biases; biases mitigations ... See more keywords

Sampling bias does not exaggerate climate–conflict claims

Sign Up to like & get
recommendations! Published in 2018 at "Nature Climate Change"

DOI: 10.1038/s41558-018-0170-5

Abstract: To the Editor — In a recent Letter, Adams and colleagues1 argue that claims regarding climate–conflict links are overstated because of sampling bias. However, this conclusion rests on logical fallacies and conceptual misunderstanding. There is… read more here.

Keywords: conflict; climate; case; sampling bias ... See more keywords

Sampling bias and incorrect rooting make phylogenetic network tracing of SARS-COV-2 infections unreliable

Sign Up to like & get
recommendations! Published in 2020 at "Proceedings of the National Academy of Sciences of the United States of America"

DOI: 10.1073/pnas.2007295117

Abstract: There is obvious interest in gaining insights into the epidemiology and evolution of the virus that has recently emerged in humans as the cause of the coronavirus disease 2019 (COVID-19) pandemic. The recent paper by… read more here.

Keywords: network; incorrect rooting; sampling bias; sars cov ... See more keywords

Dynamic sampling bias and overdispersion induced by skewed offspring distributions.

Sign Up to like & get
recommendations! Published in 2021 at "Genetics"

DOI: 10.1093/genetics/iyab135

Abstract: Natural populations often show enhanced genetic drift consistent with a strong skew in their offspring number distribution. The skew arises because the variability of family sizes is either inherently strong or amplified by population expansions.… read more here.

Keywords: frequency; genetics; time; offspring distributions ... See more keywords
Photo by mbaumi from unsplash

Using data from related species to overcome spatial sampling bias and associated limitations in ecological niche modelling

Sign Up to like & get
recommendations! Published in 2017 at "Methods in Ecology and Evolution"

DOI: 10.1111/2041-210x.12832

Abstract: Ecological niche modelling (ENM) is used widely to aid in conservation planning and management, often focusing on rare species characterized by the biased observations associated with restricted geographic ranges, habitat specialization, small population size and… read more here.

Keywords: niche modelling; ecological niche; sampling bias; spatial sampling ... See more keywords

Model‐based ordination for phenological studies: From controlling sampling bias to inferring temporal associations

Sign Up to like & get
recommendations! Published in 2025 at "Methods in Ecology and Evolution"

DOI: 10.1111/2041-210x.70079

Abstract: Willig et al. (Methods in Ecology and Evolution, 15, 868–885, 2024) cautioned that unequal sampling effort and pseudoreplication can bias the characterisation of species phenology using circular statistics. Borrowing concepts from rarefaction, they proposed bootstrapping… read more here.

Keywords: sampling bias; ecology; based ordination; model based ... See more keywords

Dealing with sampling bias and inferring absence data to improve distribution models of a widely distributed vulnerable marsupial

Sign Up to like & get
recommendations! Published in 2024 at "Austral Ecology"

DOI: 10.1111/aec.13474

Abstract: Species distribution models are widely used to identify potential and high‐quality habitat of endangered species to inform conservation decisions. However, their usefulness is constrained by the amount and quality of biodiversity data and the approaches… read more here.

Keywords: distribution; presence; absence; sampling bias ... See more keywords

Effective strategies for correcting spatial sampling bias in species distribution models without independent test data

Sign Up to like & get
recommendations! Published in 2024 at "Diversity and Distributions"

DOI: 10.1111/ddi.13802

Abstract: Spatial sampling bias (SSB) is a feature of opportunistically sampled species records. Species distribution models (SDMs) built using these data (i.e. presence‐background models) can produce biased predictions of suitability across geographic space, confounding species occurrence… read more here.

Keywords: distribution; distribution models; spatial sampling; sampling bias ... See more keywords