The DOI matches its Crossref record; 91 of the 91 references it cites were found in a registry or an index.
So Many Variables: Joint Modeling in Community Ecology
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Citations
Cites
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Longitudinal data analysis using generalized linear models
LIANG, K.-Y., & ZEGER, S. L. (1986) · Biometrika · doi:10.1093/biomet/73.1.13 · Cited by 18,550
A new method for non-parametric multivariate analysis of variance
Anderson, M. J. (2001) · Austral Ecology · doi:10.1111/j.1442-9993.2001.01070.pp.x · Cited by 13,828
Generalized linear mixed models: a practical guide for ecology and evolution
Bolker, B. M., Brooks, M. E., Clark, C. J., Geange, S. W., Poulsen, J. R., Stevens, M. H. H., & White, J.-S. S. (2009) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2008.10.008 · Cited by 8,910
Multidimensional Scaling by Optimizing Goodness of Fit to a Nonmetric Hypothesis
Kruskal, J. B. (1964) · Psychometrika · doi:10.1007/bf02289565 · Cited by 7,317
Sparse inverse covariance estimation with the graphical lasso
Friedman, J., Hastie, T., & Tibshirani, R. (2008) · Biostatistics · doi:10.1093/biostatistics/kxm045 · Cited by 6,355
The ade4 Package: Implementing the Duality Diagram for Ecologists
Dray, S., & Dufour, A.-B. (2007) · Journal of Statistical Software · doi:10.18637/jss.v022.i04 · Cited by 6,211
WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility
Lunn, D. J., Thomas, A., Best, N., & Spiegelhalter, D. (2000) · Statistics and Computing · doi:10.1023/a:1008929526011 · Cited by 5,368
Rue, H., Martino, S., & Chopin, N. (2009) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2008.00700.x · Cited by 5,279
JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling
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Cited by
Guillera‐Arroita, G. (2017) · Ecography · doi:10.1111/ecog.02445 · Cited by 426
Thorson, J. T. (2019) · Fisheries Research · doi:10.1016/j.fishres.2018.10.013 · Cited by 304
Testing species assemblage predictions from stacked and joint species distribution models
Zurell, D., Zimmermann, N. E., Gross, H., Baltensweiler, A., Sattler, T., & Wüest, R. O. (2020) · Journal of Biogeography · doi:10.1111/jbi.13608 · Cited by 153
Borges, F. O., Guerreiro, M., Santos, C. P., Paula, J. R., & Rosa, R. (2022) · Frontiers in Marine Science · doi:10.3389/fmars.2022.1018766 · Cited by 28
“In this sense, the inclusion of dissolved oxygen, pH, and the distribution and ecological relationships between the OVSC species and potential predators and competitors would contribute towards more ecologically relevant models (Warton et al., 2015; Abdulwahab et al., 2022).”
BackgroundMultiple stressors in river networks: local and downstream effects on freshwater macroinvertebrates
Burgazzi, G., Juvigny‐Khenafou, N. P. D., Schreiner, V. C., Manfrin, A., Jupke, J., Piggott, J., Harvey, E., Terui, A., Leese, F., & Schäfer, R. B. (2026) · Ecography · doi:10.1002/ecog.07758 · Cited by 5
Metadata
- Authors
- Warton, D. I., Blanchet, F. G., O’Hara, R. B., Ovaskainen, O., Taskinen, S., Walker, S. C., & Hui, F. K. C.
- Venue
- Trends in Ecology & Evolution
- Publisher
- Elsevier BV
- Published
- 2015-12
- Volume
- 30
- Issue
- 12
- Pages
- 766-779
- ISSN
- 0169-5347 (ISSN-L)
- OpenAlex
- W1920817623
- Cited by
- 854
- References
- 91
- FWCI
- 3.94
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: So Many Variables: Joint Modeling in Community Ecology. https://app.cochat.ai/papers/10.1016/j.tree.2015.09.007
- The paper
- Warton, D. I., Blanchet, F. G., O’Hara, R. B., Ovaskainen, O., Taskinen, S., Walker, S. C., & Hui, F. K. C. (2015). So Many Variables: Joint Modeling in Community Ecology. Trends in Ecology & Evolution. https://doi.org/10.1016/j.tree.2015.09.007
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
