semPower.aPriori: semPower.aPriori

In semPower: Power Analyses for SEM

Description

Determine required sample size given alpha, beta/power, df, and effect

Usage

semPower.aPriori(
  effect = NULL,
  effect.measure = NULL,
  alpha,
  beta = NULL,
  power = NULL,
  N = NULL,
  df,
  p = NULL,
  SigmaHat = NULL,
  Sigma = NULL
)

Arguments

effect	effect size specifying the discrepancy between H0 and H1 (a list for multiple group models)
effect.measure	type of effect, one of "F0", "RMSEA", "Mc", "GFI", AGFI"
alpha	alpha error
beta	beta error; set either beta or power
power	power (1-beta); set either beta or power
N	a list of sample weights for multiple group power analyses, e.g. list(1,2) to make the second group twice as large as the first one
df	the model degrees of freedom
p	the number of observed variables, required for effect.measure = "GFI" and "AGFI"
SigmaHat	model implied covariance matrix (a list for multiple group models). Use in conjuntion with Sigma to define effect and effect.measure.
Sigma	population covariance matrix (a list for multiple group models). Use in conjuntion with SigmaHat to define effect and effect.measure.

Value

list

Examples

## Not run: 
power <- semPower.aPriori(effect = .05, effect.measure = "RMSEA", alpha = .05, beta = .05, df = 200)
summary(power)
power <- semPower.aPriori(effect = .15, effect.measure = "F0", alpha = .05, power = .80, df = 100)
summary(power)
power <- semPower.aPriori(effect = list(.05, .10), effect.measure = "F0", alpha = .05, 
                          power = .80, N = list(1, 1), df = 100)
summary(power)
power <- semPower.aPriori(alpha = .01, beta = .05, df = 5, 
                          SigmaHat = diag(4), Sigma = cov(matrix(rnorm(4*1000),  ncol=4)))
summary(power)

## End(Not run)

semPower documentation built on Nov. 2, 2021, 1:06 a.m.