Description Usage Arguments Details Author(s) Source See Also Examples
Extract simulated quantities of interest from a zelig object
1 | 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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | #### 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))
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