Changing the support of a spatial covariate: A simulation study

Tisha Hooks, Jeffrey F. Pedersen, David B. Marx, Roch E. Gaussoin

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Researchers are increasingly able to capture spatially referenced data on both a response and a covariate more frequently and in more detail. A combination of geostatisical models and analysis of covariance methods may be used to analyze such data. However, very basic questions regarding the effects of using a covariate whose support differs from that of the response variable must be addressed to utilize these methods most efficiently. In this experiment, a simulation study was conducted to assess the following: (i) the gain in efficiency when geostatistical models are used, (ii) the gain in efficiency when analysis of covariance methods are used, and (iii) the effects of including a covariate whose support differs from that of the response variable in the analysis. This study suggests that analyses which both account for spatial structure and exploit information from a covariate are most powerful. Also, the results indicate that the support of the covariate should be as close as possible to the support of the response variable to obtain the most accurate experimental results.

Original languageEnglish (US)
Pages (from-to)622-628
Number of pages7
JournalCrop Science
Volume47
Issue number2
DOIs
StatePublished - Mar 1 2007
Externally publishedYes

ASJC Scopus subject areas

  • Agronomy and Crop Science

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    Hooks, T., Pedersen, J. F., Marx, D. B., & Gaussoin, R. E. (2007). Changing the support of a spatial covariate: A simulation study. Crop Science, 47(2), 622-628. https://doi.org/10.2135/cropsci2006.07.0490