2018
DOI: 10.21105/joss.00772
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ggeffects: Tidy Data Frames of Marginal Effects from Regression Models

Abstract: Results of regression models, like estimates, are typically presented as tables that are easy to understand. Sometimes pure estimates are not helpful and difficult to interpret. This is especially true for interaction terms in logistic regression or even more complex models, or transformed terms (quadratic or cubic terms, polynomials, splines), where the estimates are no longer interpretable in a direct way. In such cases, marginal effects are far easier to understand. In particular, the visualization of margi… Show more

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Cited by 1,681 publications
(1,052 citation statements)
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“…Confidence intervals of fixed effect parameter estimates were obtained using the profile likelihood method implemented in the confint.merMod function of the lme4 package. The function ggpredict from the ggeffects package (Lüdecke ) was used to compute predicted marginal effects of year on measurements of pollinator visitation holding number of flowers per patch fixed.…”
Section: Methodsmentioning
confidence: 99%
“…Confidence intervals of fixed effect parameter estimates were obtained using the profile likelihood method implemented in the confint.merMod function of the lme4 package. The function ggpredict from the ggeffects package (Lüdecke ) was used to compute predicted marginal effects of year on measurements of pollinator visitation holding number of flowers per patch fixed.…”
Section: Methodsmentioning
confidence: 99%
“…We calculated a GLMM with accuracy, solution time, search, and search effort and un/related prime as fixed effects. The output summary and the p ‐values for the single predictors were obtained via the sjPlot‐package in R (Lüdecke, ).…”
Section: Methodsmentioning
confidence: 99%
“…All analyses were conducted in R software version 3.4.4 [20]. Logistic regression modelling was conducted using the 'glm' function and predicted probabilities were computed using 'ggaverage' from the 'ggeffects' package [21].…”
Section: Statistical Modelling Analysesmentioning
confidence: 99%