The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Analysis of Unbalanced Data by Mixed Linear Models Using the mixed Procedure of the SAS System
Abstract
Unbalanced data are a common problem in plant research based on designed experiments. Such data are often conveniently analysed using linear mixed models. Recent developments in mixed model theory have been implemented in major packages. This paper describes the use of the mixed procedure of the SAS System for the analysis of designed experiments. Special emphasis is given to the specification of options as depending on the assumed mixed model and on the unbalancedness in the data. In addition, we consider a compact representation of multiple comparisons for unbalanced data (letter display). Two small data sets are used to exemplify the methods.
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Small sample inference for fixed effects from restricted maximum likelihood
Kenward, M. G., & Roger, J. H. (1997) · Biometrics · doi:10.2307/2533558 · Cited by 4,552
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Searle, S. R., Casella, G., & McCulloch, C. E. (1992) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316856 · Cited by 1,926
Flagged first, then by citations
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Buçinca, Z., Malaya, M. B., & Gajos, K. Z. (2021) · arXiv · doi:10.48550/arxiv.2102.09692 · Cited by 1,124
“Mixed-effects models also properly handle the imbalance in our data [57], due to participants being randomly assigned to conditions and not all participants having”
Method
Metadata
- Authors
- Spilke, J., Piepho, H. P., & Hu, X.
- Affiliations
- University of Hohenheim (DE)
- Corresponding author
- Spilke, J.
- Piepho, H. P.
- Hu, X.
- ORCID
- Venue
- Journal of Agronomy and Crop Science
- Publisher
- Wiley
- Published
- 2005-02
- Volume
- 191
- Issue
- 1
- Pages
- 47-54
- ISSN
- 0931-2250 (ISSN-L)
- 1439-037X
- OpenAlex
- W2105697681
- Cited by
- 116
- References
- 3
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 8 · 2023: 3 · 2022: 7 · 2021: 8 · 2020: 7 · 2019: 3 · 2018: 3 · 2017: 2 · 2016: 6 · 2015: 8 · 2014: 4 · 2013: 9 · 2012: 6
- FWCI
- 6.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Agronomy and Crop Science (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Computer Science › Software › SAS software applications and methods
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Keywords
- class imbalance, linear mixed models, designed experiments, multiple comparisons
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