frames

0th

Percentile

Average Marginal Effects

Provides the average marginal effects of a GLM model with bootstrapped confidence intervals. Similar results would be obtained from using margins::margins().

Usage
frames(model, ci_type = "perc", boot = 100, ci = 0.95)
Arguments
model

the model object

ci_type

the type of boostrapped confidence interval; options are "perc", "basic", "bca"

boot

the number of bootstrapped samples; default is 100

ci

the confidence interval; the default is .975 which is the 95% confidence interval.

Details

Using the average marginal effects as discussed by Tamas Bartus (2005), the coefficients are transformed into probabilities (for binary outcomes) or remain in their original units (continuous outcomes).

References

Bartus, T. (2005). Estimation of marginal effects using margeff. The Stata Journal, 5(3), 309<U+2013>329. <https://EconPapers.repec.org/RePEc:tsj:stataj:v:5:y:2005:i:3:p:309-329>

Aliases
  • frames
Examples
# NOT RUN {
library(furniture)
data(nhanes_2010)
fit = glm(marijuana ~ home_meals + gender + age + asthma, 
           data = nhanes_2010, 
           family = "binomial")
frames(fit)


# }
Documentation reproduced from package MarginalMediation, version 0.5.1, License: GPL-2

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