Statistical procedures most used in the analysis of measures repeated in time in the agricultural sector
Article Sidebar
Main Article Content
Abstract
strategies are more appropriate for each purpose. In this study, three types of traditionally used analyses are described: univariate variance (ANOVA), multivariate variance (MANOVA), and the recent one, the approach of mixed models. At present, it has been agreed that the latter is the most adequate and versatile, because it provides the possibility of examining data with structures of dependence, unbalance, and lack of normality. Besides, it provides a solution to the limitation of the multivariate analysis of variance in respect to the number of individuals and variables. Also, the model of random effects is described, another member of the wide spectrum of the mixed models that is used in numerous studies in the agricultural field. This approach is strengthened by the use of selection criteria of models, due to the estimation of parameters is based on methods of maximum likelihood or restricted maximum likelihood. The Akaike information criterion (AIC) and the
Bayesian information criterion (BIC) are described, permitting the optimum selection of competing mixed models.
Key words: repeated measures, univariate analysis, multivariate analysis, mixed models, information criteria.
Article Details
Those authors that have publications with this journal accept the following terms:
1. They will retain their copyright and guarantee the journal the right of first publication of their work, which will be simultaneously subject to the License Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) that allows third parties to share the work whenever its author is indicated and its first publication this journal. Under this license the author will be free of:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
2. The authors may adopt other non-exclusive license agreements to distribute the published version of the work (e.g., deposit it in an institutional telematics file or publish it in a monographic volume) whenever the initial publication is indicated in this journal.
3. The authors are allowed and recommended disseminating their work through the Internet (e.g. in institutional telematics archives or on their website) before and during the submission process, which can produce interesting exchanges and increase the citations of the published work. (See the Effect of open access).