Journal ArticleDOI
Accounting for natural and extraneous variation in the analysis of field experiments.
TLDR
The authors identify three major components of spatial variation in plot errors from field experiments and extend the two-dimensional spatial procedures of Cullis and Gleeson (1991) to account for them.Abstract:
We identify three major components of spatial variation in plot errors from field experiments and extend the two-dimensional spatial procedures of Cullis and Gleeson (1991) to account for them. The components are nonstationary, large-scale (global) variation across the field, stationary variation within the trial (natural variation or local trend), and extraneous variation that is often induced by experimental procedures and is predominantly aligned with rows and columns. We present a strategy for identifying a model for the plot errors that uses a trellis plot of residuals, a perspective plot of the sample variogram and, where possible, likelihood ratio tests to identify which components are present. We demonstrate the strategy using two illustrative examples. We conclude that although there is no one model that adequately fits all field experiments, the separable autoregressive model is dominant. However, there is often additional identifiable variation present.read more
Citations
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Journal ArticleDOI
On the design of early generation variety trials with correlated data
TL;DR: In this article, the authors considered the design of early generation variety trials with a prespecified spatial correlation structure and introduced a new class of partially replicated designs called p-rep designs in which the plots of standard varieties are replaced by additional plots of test lines.
Journal ArticleDOI
The Analysis of Designed Experiments and Longitudinal Data by Using Smoothing Splines
TL;DR: In this paper, the cubic smoothing spline is used in conjunction with fixed and random effects, random coefficients and variance modelling to provide simultaneous modelling of trends and covariance structure, which allows coherent and flexible empirical model building in complex situations.
Journal ArticleDOI
Heat and drought adaptive QTL in a wheat population designed to minimize confounding agronomic effects
R. Suzuky Pinto,Matthew P. Reynolds,Ky L. Mathews,C. Lynne McIntyre,Juan-Jose Olivares-Villegas,Scott Chapman +5 more
TL;DR: Yield QTL were shown to be associated with components of other traits, supporting the prospects for dissecting crop performance into its physiological and genetic components in order to facilitate a more strategic approach to breeding.
References
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Book
Statistics for spatial data
Noel A Cressie,Noel A Cressie +1 more
TL;DR: In this paper, the authors present a survey of statistics for spatial data in the field of geostatistics, including spatial point patterns and point patterns modeling objects, using Lattice Data and spatial models on lattices.
Book
Analysis of longitudinal data
TL;DR: In this paper, a generalized linear model for longitudinal data and transition models for categorical data are presented. But the model is not suitable for categric data and time dependent covariates are not considered.
Journal ArticleDOI
Small Sample Inference for Fixed Effects from Restricted Maximum Likelihood
TL;DR: A scaled Wald statistic is presented, together with an F approximation to its sampling distribution, that is shown to perform well in a range of small sample settings and has the advantage that it reproduces both the statistics and F distributions in those settings where the latter is exact.