wsMed (version 1.0.2)

analyze_mm_continuous: Conditional Indirect Effects with a Continuous Moderator

Description

Summarises Monte-Carlo draws from a semmcci object when the moderator W is continuous. The function outputs:

1. mod_coeff – table of every moderated path coefficient (aw, bw, dw, cpw) with its base counterpart and 95 % CI;

2. beta_coef – indirect effect at three reference points of W (–1 SD, mean, +1 SD);

3. path_HML – likewise, the moderated primary paths (a, b, …) at the three W levels;

4. theta_curve – full curve of the indirect effect over a user-defined grid of centred W;

5. path_curve – full curve for every moderated base path.

Significance stars ("*") are added where the CI excludes 0.

Usage

analyze_mm_continuous(
  mc_result,
  data,
  MP,
  W_raw_name = "W",
  ci_level = 0.95,
  W_values = NULL,
  n_curve = 120,
  digits = 8
)

Value

A named list with components:

mod_coeff

Moderated path coefficients (aw, bw, …).

beta_coef

Indirect effect at –1 SD / 0 SD / +1 SD.

path_HML

Moderated base paths at the three W levels.

theta_curve

Data frame of the indirect effect curve.

path_curve

Data frame of each moderated base-path curve.

Arguments

mc_result

A semmcci object returned by MCMI2().

data

A processed data frame (first element of PrepareData() output) that contains the raw moderator column.

W_raw_name

Name of the moderator column in data. Default "W".

ci_level

Two-sided confidence level (default 0.95).

W_values

Numeric vector of raw W values at which to evaluate “Low / Mid / High” effects. If NULL (default) the vector \(mean(W) ± 1\,SD\) is used.

n_curve

Integer, number of points used to draw the continuous effect curve (default 120).

digits

Integer, decimal places for rounding (default 3).