Stevia rebaudiana (Bert) Bertoni: regression models with mixed effects for investigating seed germination data

Edilenia Queiroz Pereira, Vanderly Janeiro, Terezinha Aparecida Guedes, José Walter Pedroza Carneiro


We investigated regression models with mixed effects using generalized linear statistics to evaluate germination data from Stevia rebaudiana (Bert) Bertoni. Estimates and validation of statistical parameters were conducted using the “gamlss” package in the R software. Generalized linear mixed effects followed the binomial, the beta-binomial and the multinomial distribution with the logit link to explain data based on the following explanatory variables: seed germinator, plastic tray position on every tier of shelves, illuminance conditions (light and darkness) and seed lots. We did not find differences in proportional responses from seed germinators, but we did find differences in the illuminance conditions, plastic tray position on the tiers of shelves in the seed germinators and seed lots. The estimates of the generalized Akaike information criterion (GAIC), Akaike information criterion (AIC), global deviance (GD) and Bayesian information criterion of Schwarz (BIC) indicate similar goodness-of-fit for the binomial and beta-binomial models. All of the models indicate that the position of the germination tray on every tier of shelves and illuminance conditions affected the proportions of normal seedlings. The seed germination in the plastic tray on the uppermost position under fluorescent day light lamps had an effect on the proportion of normal seedlings of Stevia.



binomial; beta-binomial; multinomial; gamlss; mixed effects.

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