# frames

##### 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>

##### 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*