Tidy a(n) mediate object

Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

# S3 method for mediate
tidy(x, conf.int = FALSE, conf.level = 0.95, ...)

Arguments

x	A mediate object produced by a call to mediation::mediate().
conf.int	Logical indicating whether or not to include a confidence interval in the tidied output. Defaults to FALSE.
conf.level	The confidence level to use for the confidence interval if conf.int = TRUE. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval.
...	Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.level = 0.9, all computation will proceed using conf.level = 0.95. Additionally, if you pass newdata = my_tibble to an augment() method that does not accept a newdata argument, it will use the default value for the data argument.

Details

The tibble has four rows. The first two indicate the mediated effect in the control and treatment groups, respectively. And the last two the direct effect in each group.

See also

tidy(), mediation::mediate()

Value

A tibble::tibble() with columns:

conf.high

Upper bound on the confidence interval for the estimate.

conf.low

Lower bound on the confidence interval for the estimate.

estimate

The estimated value of the regression term.

p.value

The two-sided p-value associated with the observed statistic.

statistic

The value of a T-statistic to use in a hypothesis that the regression term is non-zero.

std.error

The standard error of the regression term.

term

The name of the regression term.

Examples

library(mediation)
#> Registered S3 methods overwritten by 'Hmisc':
#>   method          from      
#>   summary.formula ergm      
#>   vcov.default    fit.models
#> Registered S3 methods overwritten by 'lme4':
#>   method                          from
#>   cooks.distance.influence.merMod car 
#>   influence.merMod                car 
#>   simulate.formula                ergm
#>   dfbeta.influence.merMod         car 
#>   dfbetas.influence.merMod        car 
#> mediation: Causal Mediation Analysis
#> Version: 4.5.0
#> 
#> Attaching package: ‘mediation’
#> The following object is masked from ‘package:psych’:
#> 
#>     mediate
data(jobs)

b <- lm(job_seek ~ treat + econ_hard + sex + age, data = jobs)
c <- lm(depress2 ~ treat + job_seek + econ_hard + sex + age, data = jobs)
mod <- mediate(b, c, sims = 50, treat = "treat", mediator = "job_seek")

tidy(mod)
#> # A tibble: 4 x 4
#>   term   estimate std.error p.value
#>   <chr>     <dbl>     <dbl>   <dbl>
#> 1 acme_0  -0.0143    0.0129    0.24
#> 2 acme_1  -0.0143    0.0129    0.24
#> 3 ade_0   -0.0315    0.0377    0.24
#> 4 ade_1   -0.0315    0.0377    0.24
tidy(mod, conf.int = TRUE)
#> # A tibble: 4 x 6
#>   term   estimate std.error p.value conf.low conf.high
#>   <chr>     <dbl>     <dbl>   <dbl>    <dbl>     <dbl>
#> 1 acme_0  -0.0143    0.0129    0.24  -0.0349    0.0103
#> 2 acme_1  -0.0143    0.0129    0.24  -0.0349    0.0103
#> 3 ade_0   -0.0315    0.0377    0.24  -0.105     0.0584
#> 4 ade_1   -0.0315    0.0377    0.24  -0.105     0.0584
tidy(mod, conf.int = TRUE, conf.level = .99)
#> # A tibble: 4 x 6
#>   term   estimate std.error p.value conf.low conf.high
#>   <chr>     <dbl>     <dbl>   <dbl>    <dbl>     <dbl>
#> 1 acme_0  -0.0143    0.0129    0.24  -0.0378    0.0243
#> 2 acme_1  -0.0143    0.0129    0.24  -0.0378    0.0243
#> 3 ade_0   -0.0315    0.0377    0.24  -0.106     0.0686
#> 4 ade_1   -0.0315    0.0377    0.24  -0.106     0.0686