Invited review: Integrating quantitative findings from multiple studies using mixed model methodology.

By N. St-Pierre. Journal of Dairy Science, 2001

835 citations recorded by the source corpus.

Subfields: Agronomy and Crop Science, Environmental Chemistry, Genetics

View Paper: https://www.semanticscholar.org/paper/4de271bca51f14e391fda12686c9f187d4c6b3e2

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Citations in the corpus

Evaluation and application of the CPM Dairy Nutrition model (2007, methodology): “When the random study effects were removed from the observed DMI and regressed against model-predicted DMI (St-Pierre 2001), an R2 of 0.63, root of mean square error (MSE) of 2.62 kg/d, mean bias of 2.14 kg/d (P 0.001), root of MSEP of 3.4 kg/d (0.15 of the observed mean) and model accuracy (as…”
Adaptive abilities of the females and sustainability of ruminant livestock systems. A review (2006, background): “An interesting way could be to use metaanalyses that allow to integrate knowledge and quantify the response from the findings from a collection of studies [67, 71].”
Effects of grain variability and processing on starch utilization by lactating dairy cattle (2001, methodology): “Our statistical procedures (St-Pierre, 2001) have taken trial effects into consideration (see next section) and should provide safer conclusions among treatments that were not compared within trial (hereafter termed experiment).”
Effects of stocking rate, supplementation, genotype and their interactions on grazing dairy systems: a review (2010, methodology): “As suggested by St-Pierre ( 2001 ), study was fitted as a random effect.”
A meta-analysis of the impact of stocking rate on the productivity of pasture-based milk production systems (2010, methodology): “Statistical analysis A study effect (IdExp) representing the variance between studies not accounted for by the variables in the model was included in each model, as described by St-Pierre (2001) and more recently by Sauvant et al. (2008).”
Voluntary feed intake and digestibility of four domestic ruminant species as influenced by dietary constituents: A meta-analysis (2014, methodology): “Data were analysed using mixed model regression methodology (St-Pierre, 2001; Sauvant et al., 2008).”
Prediction of enteric methane production, yield and intensity of beef cattle using an intercontinental database (2019, background): “random study effect will affect the inference made on the covariates and may result in type II errors 563 (St-Pierre, 2001).”