Print a summary of the estimated multilevel mediation model

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Description

Prints the estimated parameters (numerical summaries of the marginal posterior distributions).

Usage

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mlm_summary(mod = NULL, level = 0.95, pars = c("a", "b", "cp", "ab", "c",
  "pme", "covab", "corrab"), digits = 2)

Arguments

mod

A stanfit object obtained from mlm()

level

"Confidence" level; Defines the limits of the credible intervals. Defaults to .95 (i.e. displays 95% CIs.)

pars

Parameters to summarize. Defaults to main average-level parameters. See Details for more information.

digits

How many decimal points to display in the output. Defaults to 2.

Details

After estimating a model (drawing samples from the joint posterior probability distribution) with mlm(), show the estimated results by using mlm_summary(fit), where "fit" is an object containing the fitted model.

The function shows, for each parameter specified with pars, the posterior mean, and limits of the Credible Interval as specified by level. For example, level = .91 shows a 91% Credible Interval, which summarizes the central 91% mass of the marginal posterior distribution.

Parameters

By default, mlm() estimates and returns a large number of parameters, including the varying effects, and their associated standard deviations. However, mlm_summay() by default only displays a subset of the estimated parameters:

a

Regression slope of the X -> M relationship.

b

Regression slope of the M -> Y relationship.

cp

Regression slope of the X -> Y relationship. (The direct effect.)

ab

Mediated effect (a * b).

c

Total effect of X on Y. ( cp + ab + σ_ab )

pme

Percent mediated effect.

covab

Estimated covariance of the participant-level a_j and b_j parameters.

corrab

Estimated correlation of the participant-level a_j and b_j parameters.

The user may specify pars = NULL to display all estimated parameters. Other options include e.g. pars = "tau" to display the varying effects' standard deviations.

To learn more about the additional parameters, refer to the Stan code (cat(get_stancode(fit))).

Value

A data.frame summarizing the estimated multilevel mediation model:

Parameter

Name of parameter

Mean

Mean of parameter's posterior distribution.

Median

Median of parameter's posterior distribution.

SD

Standard deviation of parameter's posterior distribution.

ci_lwr

The lower limit of Credible Intervals.

ci_upr

The upper limit of Credible Intervals.

n_eff

Number of efficient samples.

Rhat

Should be 1.00.

Author(s)

Matti Vuorre mv2521@columbia.edu