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3 results for “Beta regression”

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dryad36/100

Data from: Trends in plant cover derived from vegetation-plot data using ordinal zero-augmented beta regression

<p><strong>Questions.</strong> Plant cover values in vegetation-plot data are bounded between 0 and 1, and cover is typically recorded in discrete classes with non-equal intervals. Consequently, cover data are skewed and heteroskedastic, which hampers the application of conventional regression methods. Recently developed ordinal beta regression models consider these statistical difficulties. Our primary question is if we can detect species trends in vegetation-plot time series data with this modelling approach. A second question is whether trends in cover have additional value compared to trends in occurrence, which are easier to assess for practitioners.</p> <p><strong>Location</strong>. The Netherlands, Western Europe.</p> <p><strong>Methods. </strong>We used vegetation-plot data collected from 10.000 fixed plots which were surveyed once every four years during 1999-2022. We used the ordinal zero-augmented beta regression (OZAB) model, a hierarchical model consisting of a logistic regression for presence and an ordinal beta regression for cover. We adapted the OZAB model for longitudinal data and produced estimates of cover and occurrence for each four-year period. Thereafter we assessed trends in cover and in occurrence across all periods.</p> <p><strong>Results.</strong> We found evidence of a trend in cover in 318 out of the 721 species (44%) with sufficient data. Most species showed similar directional trends in occurrence and percent cover. No trend in occurrence was detected for 64 species that had evidence of a trend in cover. Declining species had stronger relative changes in cover than in occurrence.</p> <p><strong>Conclusions. </strong>Our model enables researchers to detect trends in cover using longitudinal vegetation-plot data. Cover trends often corroborated trends in occurrence, but we also regularly found trends in cover even in the absence of evidence for trends in occurrence. Our approach thus contributes to a more complete picture of (changes in) vegetation composition based on large monitoring datasets.</p>

opencc-zeroJun 2024View details →
dryad36/100

Data from: Trends in plant cover derived from vegetation-plot data using ordinal zero-augmented beta regression

Open the record for dataset details and reuse information.

publicJun 2024View details →
zenodo24/100

A Two-Stage Research Performance Assessment of Turkish Higher Education Institutions Using Data Envelopment Analysis and Beta Regression

<p>Raw&nbsp;data used in the first and second stage of our analysis.</p>

opencc-by-4.0Mar 2022View details →

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DANDI Archive for NWB datasets

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dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

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Last verified 2026-04-29Open record

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neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record