Model based inference in the life sciences: A primer on evidence, by David R. Anderson
By G. Suter. 2009
145 citations recorded by the source corpus.
Subfields: Ecological Modeling
View Paper: https://www.semanticscholar.org/paper/28e8cf843e7535a8a0c50cf1bdb9969dd8abd226
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Ecological Modeling
- Werner Ulrich
- Catherine H. Graham
- Nicholas Gotelli
- Shinichi Nakagawa
- Jeannine Cavender-Bares
- V. Calcagno
- C. Mazancourt
- Bryan C. Carstens
Citations in the corpus
- Elevated reproductive effort increases blood parasitaemia and decreases immune function in birds: a meta-regression approach (2009, methodology): “Therefore, we used meta-regression analyses using an information theoretic approach based on AIC corrected for small sample size (AICc; Burnham & Anderson 2002; Anderson 2008), to avoid model selection based on heterogeneity statistics, which has been used traditionally (Cooper & Hedges 1994).”
- Phylogeography's past, present, and future: 10 years after Avise, 2000. (2010, background): “Under either approach, any one competing model is never ‘‘true” but instead is a useful approximation that should capture the essential features of a demographic history and is most useful if it is somewhat robust to violation of model assumptions (Anderson, 2007; Wakeley, 2004).”
- glmulti: An R Package for Easy Automated Model Selection with (Generalized) Linear Models (2010, methodology): “Synthetic statistics of the confidence set of models (e.g., multi-model parameter estimates, relative support for the variables, etc.) are expected to be more robust (Anderson 2008).”
- Statistical challenges in null model analysis (2012, methodology): “Information criteria assign probabilities to competing models with diff erent numbers of free parameters and thus allow for a ranking of models from best to worst (Anderson 2008).”
- Holding up a mirror to the society: Children recognize exotic species much more than local ones (2013, methodology): “Model selection was based on Akaike’s Information Criterion (AIC); the model with the lowest AIC value was considered as the best compromise between model deviance and model parameters (Anderson, 2008).”