Remedies for pseudoreplication

By R. Millar, Marti J. Anderson. 2004

277 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/64b8f0d3b04cb1f8a4291bf9b5909e328d5acb77

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. José M. Herrera
2. Daniel García
3. Stanley E. Lazic

In Environmental Engineering

1. Daniel García
2. Stanley E. Lazic
3. L. Buisson
4. G. Grenouillet
5. L. Blanc

In Nature and Landscape Conservation

1. G. Grenouillet
2. L. Buisson
3. José M. Herrera
4. Daniel García
5. Stanley E. Lazic
6. L. Blanc
7. Regino Zamora
8. L. Gómez‐Aparicio

Citations in the corpus

• The role of remnant trees in seed dispersal through the matrix: Being alone is not always so sad (2009, background): “the potential pseudoreplication bias associated with the fact that a portion of the individual trees was repeatedly sampled whereas another portion was replaced by the nearest neighbor tree in the second year ( Millar and Anderson, 2004 ).”
• The problem of pseudoreplication in neuroscientific studies: is it affecting your analysis? (2010, background): “Millar RB, Anderson MJ: Remedies for pseudoreplication.”
• Modelling stream fish species distribution in a river network: the relative effects of temperature versus physical factors (2008, background): “Thus the repetition of each site could lead to underestimation of standard errors and consequently, to an increase of the chance of detecting statistically significant results by inflated Type I error rate (Hurlbert 1984; Millar & Anderson 2004).”