Longitudinal model for categorical data applied in an agriculture experiment about elephant grass

Abstract

Experiments where the response is a categorical variable are usually carried out in many fields such as agriculture. In addition, in some situations this response has three or more levels without an order between them characterizing a multinomial (nominal) response. Statistical models for scenarios where the observations of a nominal response can be considered independent have an extensive literature, such as the baseline-category logit models. However, situations where this assumption is violated (as in longitudinal studies) require specific models that take into consideration the dependence between observations. In this paper, a fairly new extension of the generalized estimating equations is applied to analyze an experiment carried out to investigate the type of vegetation observed in an elephant grass pasture, according to some management conditions over time. This extension uses local odds ratios to explain the dependence among the categories of the outcome over the repeated measurements. Two different structures were compared to describe this dependence, and the Wald test was used to select the significant variables. Further, we built confidence intervals for the predicted probabilities of occurrence of each category and assessed the results comparing observed/predicted values and using the diagnostic analysis. The results allowed to conclude that there are various significant effects for treatments and for time. The structure of local odds ratio also proved as a good way to describe the dependence between categorical responses over time.

Tropical Forage Grasses Intercropped Under Lenient Grazing Intensities Promote Greater Soil Cover

“…For regions of tropical climate, there is a predominance of pastures grown in monoculture, and even if it is well managed there are reports of invasive plants coexisting with grass of agronomic interest (Menarin et al 2017). In view of this, Barbosa et al (2018) suggested a proposal for an intercropping between Panicum and Brachiaria, because in theory the combination of these two genera will occupy distinct space niches, promoting greater soil coverage through tussock and straw deposition.…”

Quasi-beta Longitudinal Regression Model Applied to Water Quality Index Data

“…In many cases, it is common to analyze data resulting from experiments in which one or more response variables are measured repeatedly in a group of individuals (Fitzmaurice et al 2008;Verbeke et al 2014). Experiments with these characteristics are called longitudinal studies and are often performed in several areas of knowledge, examples including agriculture (Menarin et al 2017), education (Kaya and Leite 2017) and medicine (Hunger et al 2012;Mohd Din et al 2014). In general, a longitudinal study allows us to evaluate changes in the response variable over time, in addition to investigating the effect of covariates (Diggle et al 2002).…”