wp.modmed.m15: model15

In johnnyzhz/WebPower: Basic and Advanced Statistical Power Analysis

model15

Description

power analysis of model 15 in Introduction to Mediation, Moderation, and Conditional Process Analysis. Powers are obtained through either the percentile bootstrap method or the Monte Carlo method. The conditional indirect effect value is a1(b1 + b2w); the conditional direct effect value is cp + d2w; the index of moderated mediation is c2b1.

Usage

wp.modmed.m15(
  a1,
  cp,
  b1,
  b2,
  d1,
  d2,
  sige12,
  sige22,
  sigx_w,
  n,
  sigx2 = 1,
  sigw2 = 1,
  nrep_power = 1000,
  alpha = 0.05,
  b = 1000,
  nb = n,
  w_value = 0,
  power_method = "product",
  simulation_method = "percentile",
  ncore = 1,
  pop.cov = NULL,
  mu = NULL,
  varnames = c("y", "x", "w", "m", "xw", "mw")
)

Arguments

a1	regression coefficient of mediator (m) on predictor (x)
cp	regression coefficient of outcome (y) on predictor (x)
b1	regression coefficient of outcome (y) on mediator (m)
b2	regression coefficient of outcome (y) on the product (mw)
d1	regression coefficient of outcome (y) on moderator (w)
d2	regression coefficient of outcome (y) on the product (xw)
sige12	variance of error in the first regression equation
sige22	variance of error in the second regression equation
sigx_w	covariance between predictor (x) and moderator (w)
n	sample size
sigx2	variance of predictor (x)
sigw2	variance of moderator (w)
nrep_power	number of replications for finding power
alpha	type 1 error rate
b	number of bootstrap iterations
nb	bootstrap sample size, default to n, used when simulation method is "percentile"
w_value	moderator level, value of w
power_method	"product" for using the indirect effect value in power calculation, or "joint" for using joint significance in power calculation
simulation_method	"percentile" for using percentile bootstrap CI in finding significance of mediation, or "MC" for using Monte Carlo CI in finding significance of mediation
ncore	number of cores to use for the percentile bootstrap method, default is 1, when ncore > 1, parallel is used
pop.cov	covariance matrix, default to NULL if using the regression coefficient approach
mu	mean vector, default to NULL if using the regression coefficient approach
varnames	name of variables for the covariance matrix

Value

power of indirect effect, direct effect, moderation, and the index of moderated mediation

Examples

test = wp.modmed.m15(a1 = 0.6, cp = 0.2, b1 = 0.3, b2 = 0.2, d1 = 0.2, d2 = 0.1,
                     sigx2 = 1, sigw2 = 1, sige12 = 1, sige22 = 1, sigx_w = 0.4,
                     w_value = 0.3, simulation_method = "MC",
                     n = 50, nrep_power = 1000, b = 1000, alpha = 0.05, ncore = 1)
print(test)

johnnyzhz/WebPower documentation built on Sept. 17, 2024, 12:13 p.m.