Main Article Content
The objective of this study was the proposal of a statistical analysis methodology that will guide the researcher by making repeated measurements over time in the same experimental unit, through a case study with legumes as a substrate in the production of in vitro gas in the agricultural and livestock field. The variable in vitro gas production was analyzed. Pearson correlation matrix was calculated, values superior to 0.82 were obtained and the existence of association among sampling days was determined. The sphericity criterion was confirmed by means of the Mauchly statistic and, in front of its failure to fulfill, the fit of the degrees of freedom was made. In the same way, normality assumption was verified
(P <0.0100) and when it was not fulfilled, a mixed generalized linear model was used for analyzing the variants of Poisson, Gamma, Binomial, Normal and Normal Log, to determine the distribution that followed the data, which in this case was Gamma. Toeplitz variance-covariance structure was selected as the one that best fits the model based on the lower values of information criteria. The verification of theoretical assumptions necessary for repeated measures defined the model to be used. The use of a mixed generalized linear model increased the accuracy of results by
properly estimating the variance-covariance structures and allowed to analyze unbalanced data. A work methodology is proposed for data processing with repeated measures over time.
Keywords: information criteria, covariance structures, correlation
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).