A Hitchhiker's guide to mixed models for randomized experiments
By Hans-Peter Piepho, A. Büchse, K. Emrich. 2003
355 citations recorded by the source corpus.
Subfields: Plant Science, Soil Science
View Paper: https://www.semanticscholar.org/paper/15ef893a9cb9efe298ff4e54ca364fc0c2024fe7
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In Plant Science
- Hans-Peter Piepho
- Arvind Kumar
- A. Büchse
- A. Melchinger
- Jens Möhring
- Chris Brien
- R. A. Bailey
- C. Richter
In Soil Science
Citations in the corpus
- Characterization of the effect of a QTL for drought resistance in rice, qtl12.1, over a range of environments in the Philippines and eastern India (2009, methodology): “Statistical analysis Mean trait values for each QTL class were obtained using PROC MIXED of SAS (SAS Institute 2002– 2003), with degrees of freedom being computed using the DDFM = KR option (Piepho et al. 2003).”
- Evaluation of smallholder pig production systems in North Vietnam: Pig production management and pig performances (2006, methodology): “In the following, systematic components of the statistical linear models applied are given, following the model notation suggested by Piepho et al. (2003), where the cross between two effects stands for the main effects and their interaction.”
- A Mixed Modelling Approach for Randomized Experiments with Repeated Measures (2004, methodology): “To accommodate repeated measures correlation structures for a random effect, we suggest to extend Patterson’s notation (Piepho et al. 2003) as follows.”
- BLUP for phenotypic selection in plant breeding and variety testing (2008, methodology): “To illustrate formulation of a mixed model, we use the syntax described in Piepho et al. (2003, 2004), which is akin to syntax used in mixed model packages.”
- Effects of soybean variety and Bradyrhizobium strains on yield, protein content and biological nitrogen fixation under cool growing conditions in Germany (2016, methodology): “…weight (TKW), protein content, protein yield, dfa and Nfix were analysed according to the basic model for a plit-plot experiment as defined by Piepho et al. (2003): esponse = I + SV + I × SV + REP : REP × I + REP × I × SV (4) The model used the following factors: REP, complete replicate; ,…”
- Analysis of Trials with Complex Treatment Structure Using Multiple Contrast Tests (2009, background): “Block effects or more complex randomization structures may be included as random effects in a linear mixed effects model, whereas the complex treatment structure remains in the fixed part (for example Piepho et al., 2003).”
- Multiple randomizations (2006, methodology): “It has similarities to the procedure that was described by Piepho et al. (2003).”