Getting the Most out of DAGassist Using Parameters
Source:vignettes/get-started.Rmd
get-started.RmdIntroduction
DAGassist() is meant to be simple and easy to use, and
most of its features can be enjoyed via a simple two-parameter
argument:
DAGassist(
dag = your_dag_model,
formula = your_regression_call
)However, DAGassist() includes several parameters for
more specific applications. This vignette explains how to use those
parameters to get the most out of
DAGassist().
formula arguments
DAGassist supports formulaic and regression-based
formula arguments.
#formulaic formula
DAGassist(
dag = dag_model,
formula = Y ~ X + C,
data = df,
exposure = "X",
outcome = "Y"
)
#imputed formula
DAGassist(
dag = dag_model,
formula = lm(Y ~ X + C, data=df)
)The two formulas above will print identical output.
imply arguments
In cases where you only want DAGassist to use the
variables explicitly called in your formula, use
imply = FALSE.
DAGassist(
dag = dag_model,
formula = lm(Y~X+C, data = df),
imply = FALSE
)
#> DAGassist Report:
#>
#> Roles:
#> variable role X Y conf med col IO dMed dCol
#> X exposure x
#> Y outcome x
#> C collider x x
#>
#> (!) Bad controls in your formula: {C}
#> Minimal controls 1: {}
#> Canonical controls: {}
#>
#> Formulas:
#> original: Y ~ X + C
#>
#> Model comparison:
#>
#> +---+----------+-----------+-----------+
#> | | Original | Minimal 1 | Canonical |
#> +===+==========+===========+===========+
#> | X | 0.908*** | 1.415*** | 1.415*** |
#> +---+----------+-----------+-----------+
#> | | (0.030) | (0.021) | (0.021) |
#> +---+----------+-----------+-----------+
#> | C | 0.475*** | | |
#> +---+----------+-----------+-----------+
#> | | (0.022) | | |
#> +===+==========+===========+===========+
#> | + p < 0.1, * p < 0.05, ** p < 0.01, |
#> | *** p < 0.001 |
#> +===+==========+===========+===========+In cases where you want DAGassist to explore all of the
causal relationships explicated in your DAG, use
imply = TRUE.
DAGassist(
dag = dag_model,
formula = lm(Y~X+C, data = df),
imply = TRUE
)
#> DAGassist Report:
#>
#> Roles:
#> variable role X Y conf med col IO dMed dCol
#> X exposure x
#> Y outcome x x
#> Z confounder x
#> M mediator x
#> C collider x x x
#> A other
#> B other
#>
#> (!) Bad controls in your formula: {C}
#> Minimal controls 1: {Z}
#> Canonical controls: {A, B, Z}
#>
#> Formulas:
#> original: Y ~ X + C
#> minimal 1 : Y ~ X + Z
#> canonical: Y ~ X + A + B + Z
#>
#> Note: DAGassist added variables not in your formula, based on the
#> relationships in your DAG, to block back-door paths
#> between X and Y.
#> - Minimal 1 added: {Z}
#> - Canonical added: {A, B, Z}
#>
#> Model comparison:
#>
#> +---+----------+-----------+-----------+
#> | | Original | Minimal 1 | Canonical |
#> +===+==========+===========+===========+
#> | X | 0.908*** | 1.256*** | 1.256*** |
#> +---+----------+-----------+-----------+
#> | | (0.030) | (0.027) | (0.026) |
#> +---+----------+-----------+-----------+
#> | C | 0.475*** | | |
#> +---+----------+-----------+-----------+
#> | | (0.022) | | |
#> +---+----------+-----------+-----------+
#> | Z | | 0.311*** | 0.309*** |
#> +---+----------+-----------+-----------+
#> | | | (0.034) | (0.033) |
#> +---+----------+-----------+-----------+
#> | A | | | 0.187*** |
#> +---+----------+-----------+-----------+
#> | | | | (0.026) |
#> +---+----------+-----------+-----------+
#> | B | | | -0.057* |
#> +---+----------+-----------+-----------+
#> | | | | (0.026) |
#> +===+==========+===========+===========+
#> | + p < 0.1, * p < 0.05, ** p < 0.01, |
#> | *** p < 0.001 |
#> +===+==========+===========+===========+DAGassist will notify you of which variables it added.
imply = FALSE by default.
omit_factors and omit_intercept
arguments
DAGassist omits factor and intercept rows by default,
but you can explicitly include them. However, if they are not included
in your DAG, DAGassist will not evaluate them, and will not
include them in the minimal or canonical models.
DAGassist(
dag = dag_model,
formula = fixest::feols(
Y ~ X + C + i(region),
data = df),
omit_factors = FALSE,
omit_intercept = FALSE
)
#> DAGassist Report:
#>
#> Roles:
#> variable role X Y conf med col IO dMed dCol
#> X exposure x
#> Y outcome x
#> C collider x x
#>
#> (!) Bad controls in your formula: {C}
#> Minimal controls 1: {}
#> Canonical controls: {}
#>
#> Note: The following regressors, which are included in the below models, were not evaluated by DAGassist because they are not nodes in the DAG:
#> {i(region)}
#>
#> Formulas:
#> original: Y ~ X + C + i(region)
#>
#> Model comparison:
#>
#> +----------------+----------+-----------+-----------+
#> | | Original | Minimal 1 | Canonical |
#> +================+==========+===========+===========+
#> | (Intercept) | 0.060 | -0.011 | -0.011 |
#> +----------------+----------+-----------+-----------+
#> | | (0.049) | (0.027) | (0.027) |
#> +----------------+----------+-----------+-----------+
#> | X | 0.908*** | 1.415*** | 1.415*** |
#> +----------------+----------+-----------+-----------+
#> | | (0.030) | (0.021) | (0.021) |
#> +----------------+----------+-----------+-----------+
#> | C | 0.474*** | | |
#> +----------------+----------+-----------+-----------+
#> | | (0.022) | | |
#> +----------------+----------+-----------+-----------+
#> | region = North | -0.030 | | |
#> +----------------+----------+-----------+-----------+
#> | | (0.069) | | |
#> +----------------+----------+-----------+-----------+
#> | region = South | -0.085 | | |
#> +----------------+----------+-----------+-----------+
#> | | (0.069) | | |
#> +----------------+----------+-----------+-----------+
#> | region = West | -0.167* | | |
#> +----------------+----------+-----------+-----------+
#> | | (0.069) | | |
#> +================+==========+===========+===========+
#> | + p < 0.1, * p < 0.05, ** p < 0.01, *** p < |
#> | 0.001 |
#> +================+==========+===========+===========+
labels arguments
You can include a label list.
labs <- list(
X = "Exposure",
C = "Collider"
)
DAGassist(
dag = dag_model,
formula = lm(
Y ~ X + C, data = df),
labels = labs
)
#> DAGassist Report:
#>
#> Roles:
#> variable role X Y conf med col IO dMed dCol
#> Exposure exposure x
#> Y outcome x
#> Collider collider x x
#>
#> (!) Bad controls in your formula: {C}
#> Minimal controls 1: {}
#> Canonical controls: {}
#>
#> Formulas:
#> original: Y ~ X + C
#>
#> Model comparison:
#>
#> +----------+----------+-----------+-----------+
#> | | Original | Minimal 1 | Canonical |
#> +==========+==========+===========+===========+
#> | Exposure | 0.908*** | 1.415*** | 1.415*** |
#> +----------+----------+-----------+-----------+
#> | | (0.030) | (0.021) | (0.021) |
#> +----------+----------+-----------+-----------+
#> | Collider | 0.475*** | | |
#> +----------+----------+-----------+-----------+
#> | | (0.022) | | |
#> +==========+==========+===========+===========+
#> | + p < 0.1, * p < 0.05, ** p < 0.01, *** p |
#> | < 0.001 |
#> +==========+==========+===========+===========+Note that the label parameter uses
modelsummary() coef_rename logic, so an
incomplete label list will not throw any errors.
DAGassist(
dag = dag_model,
formula = lm(
Y ~ X + C, data = df),
labels = labs,
imply = TRUE
)
#> DAGassist Report:
#>
#> Roles:
#> variable role X Y conf med col IO dMed dCol
#> Exposure exposure x
#> Y outcome x x
#> Z confounder x
#> M mediator x
#> Collider collider x x x
#> A other
#> B other
#>
#> (!) Bad controls in your formula: {C}
#> Minimal controls 1: {Z}
#> Canonical controls: {A, B, Z}
#>
#> Formulas:
#> original: Y ~ X + C
#> minimal 1 : Y ~ X + Z
#> canonical: Y ~ X + A + B + Z
#>
#> Note: DAGassist added variables not in your formula, based on the
#> relationships in your DAG, to block back-door paths
#> between X and Y.
#> - Minimal 1 added: {Z}
#> - Canonical added: {A, B, Z}
#>
#> Model comparison:
#>
#> +----------+----------+-----------+-----------+
#> | | Original | Minimal 1 | Canonical |
#> +==========+==========+===========+===========+
#> | Exposure | 0.908*** | 1.256*** | 1.256*** |
#> +----------+----------+-----------+-----------+
#> | | (0.030) | (0.027) | (0.026) |
#> +----------+----------+-----------+-----------+
#> | Collider | 0.475*** | | |
#> +----------+----------+-----------+-----------+
#> | | (0.022) | | |
#> +----------+----------+-----------+-----------+
#> | Z | | 0.311*** | 0.309*** |
#> +----------+----------+-----------+-----------+
#> | | | (0.034) | (0.033) |
#> +----------+----------+-----------+-----------+
#> | A | | | 0.187*** |
#> +----------+----------+-----------+-----------+
#> | | | | (0.026) |
#> +----------+----------+-----------+-----------+
#> | B | | | -0.057* |
#> +----------+----------+-----------+-----------+
#> | | | | (0.026) |
#> +==========+==========+===========+===========+
#> | + p < 0.1, * p < 0.05, ** p < 0.01, *** p |
#> | < 0.001 |
#> +==========+==========+===========+===========+