Extract simulated quantities of interest from a zelig object
Extract simulated quantities of interest from a zelig object
zelig_qi_to_df(obj)
obj |
a zelig object with simulated quantities of interest |
A simulated quantities of interest in a tidy data formatted
data.frame. This can be useful for creating custom plots.
Each row contains a simulated value and each column contains:
setx_value whether the simulations are from the base x setx or the
contrasting x1 for finding first differences.
The fitted values specified in setx including a by column if
by was used in the zelig call.
expected_value
predicted_value
For multinomial reponse models, a separate column is given for the expected
probability of each outcome in the form expected_*. Additionally, there
a is column of the predicted outcomes (predicted_value).
Christopher Gandrud
For a discussion of tidy data see https://www.jstatsoft.org/article/view/v059i10.
#### QIs without first difference or range, from covariates fitted at
## central tendencies
z.1 <- zelig(Petal.Width ~ Petal.Length + Species, data = iris,
model = "ls")
z.1 <- setx(z.1)
z.1 <- sim(z.1)
head(zelig_qi_to_df(z.1))
#### QIs for first differences
z.2 <- zelig(Petal.Width ~ Petal.Length + Species, data = iris,
model = "ls")
z.2a <- setx(z.2, Petal.Length = 2)
z.2b <- setx(z.2, Petal.Length = 4.4)
z.2 <- sim(z.2, x = z.2a, x1 = z.2a)
head(zelig_qi_to_df(z.2))
#### QIs for first differences, estimated by Species
z.3 <- zelig(Petal.Width ~ Petal.Length, by = "Species", data = iris,
model = "ls")
z.3a <- setx(z.3, Petal.Length = 2)
z.3b <- setx(z.3, Petal.Length = 4.4)
z.3 <- sim(z.3, x = z.3a, x1 = z.3a)
head(zelig_qi_to_df(z.3))
#### QIs for a range of fitted values
z.4 <- zelig(Petal.Width ~ Petal.Length + Species, data = iris,
model = "ls")
z.4 <- setx(z.4, Petal.Length = 2:4)
z.4 <- sim(z.4)
head(zelig_qi_to_df(z.4))
#### QIs for a range of fitted values, estimated by Species
z.5 <- zelig(Petal.Width ~ Petal.Length, by = "Species", data = iris,
model = "ls")
z.5 <- setx(z.5, Petal.Length = 2:4)
z.5 <- sim(z.5)
head(zelig_qi_to_df(z.5))
#### QIs for two ranges of fitted values
z.6 <- zelig(Petal.Width ~ Petal.Length + Species, data = iris,
model = "ls")
z.6a <- setx(z.6, Petal.Length = 2:4, Species = "setosa")
z.6b <- setx(z.6, Petal.Length = 2:4, Species = "virginica")
z.6 <- sim(z.6, x = z.6a, x1 = z.6b)
head(zelig_qi_to_df(z.6))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.