wp.modmed.m14: model14

In WebPower: Basic and Advanced Statistical Power Analysis

model14

Description

power analysis of model 14 in Introduction to Mediation, Moderation, and Conditional Process Analysis

Usage

wp.modmed.m14(
  a1,
  cp,
  b1,
  d1,
  b2,
  sige12,
  sige22,
  n,
  sigx_w,
  sigx2 = 1,
  sigw2 = 1,
  nrep = 1000,
  alpha = 0.05,
  b = 1000,
  nb = n,
  MCrep = 1000,
  w_value = 0,
  power_method = "product",
  simulation_method = "percentile",
  ncore = 1,
  pop.cov = NULL,
  mu = NULL,
  varnames = c("y", "x", "w", "m", "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)
d1	regression coefficient of outcome (y) on moderator (w)
b2	regression coefficient of outcome (y) on the product (mw)
sige12	variance of error in the first regression equation
sige22	variance of error in the second regression equation
n	sample size
sigx_w	covariance between predictor (x) and moderator (w)
sigx2	variance of predictor (x)
sigw2	variance of moderator (w)
nrep	number of replications for finding power
alpha	type 1 error rate
b	number of bootstrap iterations used when simulation method is "percentile"
nb	bootstrap sample size, default to n, used when simulation method is "percentile"
MCrep	number of repetitions used for finding distribution when simulation method is "MC"
w_value	moderator level
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, 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, and moderation

References

Xu, Z., Gao, F., Fa, A., Qu, W., & Zhang, Z. (2023). Statistical Power Analysis and Sample Size Planning for Moderated Mediation Models. Zhang, Z., & Yuan, K.-H. (2018). Practical Statistical Power Analysis Using Webpower and R (Eds). Granger, IN: ISDSA Press.

Examples

test = wp.modmed.m14(a1 = 0.2, cp = 0.2, b1 = 0.5, d1 = 0.5, b2 = 0.2, sigx2 = 1,
                    sigw2 = 1, sige12 = 1, sige22 = 1, sigx_w = 0.5, n = 50,
                    w_value = 0.5, simulation_method = "MC",
                    nrep = 1000, alpha = 0.05, b = 1000, ncore = 1)
print(test)

WebPower documentation built on Oct. 14, 2023, 1:06 a.m.