Confirmatory path analysis in a generalized multilevel context.

By Bill Shipley. Ecology, 2009

984 citations recorded by the source corpus.

Subfields: Food Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/37a26fa2ab43526ba8fbf2959692f0b90d3a5234

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Citations in the corpus

piecewiseSEM: Piecewise structural equation modelling in r for ecology, evolution, and systematics (2015, background): “Several approachable examples of the derivation of basis sets can be found in Shipley (2000a, 2009).”
The indicator side of tree microhabitats: A multi-taxon approach based on bats, birds and saproxylic beetles (2018, methodology): “SEMs are a generalization of path analysis that make possible the use of models with different error distributions in the same path (Shipley, 2009).”
The impact of honey bee colony quality on crop yield and farmers’ profit in apples and pears (2017, methodology): “To solve this problem, Shipley (2009, 2013) developed an alternative procedure for conducting path analysis that allows consideration of the hierarchical structure of the data called “Generalized multilevel path analysis”.”
Hormones, parasites and male mating tactics in Alpine chamois: identifying the mechanisms of life history trade-offs (2012, background): “conditional probabilistic independences implied in the directed acyclic graph of the hypothesized causal model and which can be easily generalized to deal with data having an underlying hierarchical or multilevel structure (Shipley 2009).”
Accounting for the causal basis of collinearity when measuring the effects of habitat loss versus habitat fragmentation (2016, methodology): “Because of this, it is possible to 394 use multiple regression to measure the direct, indirect, and total effects in a system by running a 395 series of models that include different combinations of predictor and response variables (Grace 396 2008, Shipley 2009).”
Spatially explicit structural equation modeling (2014, background): “Recent methodological advances have opened broad possibilities for the modeling of nonlinear relationships and other complex data structures (e.g., Grace and Bollen 2008, Shipley 2009, Clough 2012, Grace et al. 2012), but data with a spatial component remains difficult to model in a SEM framework.”
Indirect effects of habitat loss via habitat fragmentation: A cross-taxa analysis of forest-dependent species (2020, methodology): “The global fit of each structural equation model was evaluated with Fisher's C statistic, which is adequate for mixed-effect models (Shipley, 2000, 2009).”
Predation of the invasive Asian hornet affects foraging activity and survival probability of honey bees in Western Europe (2018, methodology): “Mechanism underlying bee colony mortality We used path analyses (Shipley 2009) to test causal hypotheses on the chain of demographic processes linking hornet-based disturbance with honey bee colony collapse events throughout the winter period.”
Individual optimization of reproduction in a long‐lived migratory bird: a test of the condition‐dependent model of laying date and clutch size (2011, methodology): “Functional Ecology 2010 British Ecological Society, Functional Ecology directional-separation test (d-sep tests of path models, Shipley 2009).”
Ants as indicators of environmental change and ecosystem processes (2017, methodology): “Due to the nested structure of ur data and because of the binomial distribution of the predation ata, we tested the path models after Shipley’s directional sepaation method (Shipley, 2009) within the R environment (R Core eam, 2014).”