umxPower: Test power to detect specified path values in a model.

In umx: Structural Equation Modeling and Twin Modeling in R

Test power to detect specified path values in a model.

Description

umxPower takes an input model (the model of the true data), and tests power (or determines n) to detect dropping (or changing the value) a path in this true model.

A typical target for power is 80%. Much as the accepted critical p-value is .05, this has emerged as a trade off, in this case of resources required for more powerful studies against the cost of missing a true effect. People interested in truth discourage running studies with low power: A study with 20 percent power will fail to detect real effects 80% of the time. But even with zero power, the Type-I error rate remains a nominal 5% (and with any researcher degrees of freedom, perhaps much more than that). Low powered research, then, fails to detect true effects, and generates support for random false theories about as often. This sounds silly, but empirical rates are often as low as 20% (Button, et al., 2013).

Illustration of \alpha, \beta, and power (1-\beta):

Usage

umxPower(
  trueModel,
  update = NULL,
  n = NULL,
  power = NULL,
  sig.level = 0.05,
  value = 0,
  method = c("ncp", "empirical"),
  explore = FALSE,
  digits = 2,
  plot = TRUE,
  silent = TRUE
)

Arguments

trueModel	The model with the parameters at values you expect in the population.
update	The parameter(s) to drop
n	How many subjects? (Default = NULL)
power	Default = NULL (conventional level = .8)
sig.level	Default = .05
value	Value of dropped parameter (default = 0)
method	"ncp" (default) or "empirical"
explore	Whether to tabulate the range of n or effect size (if n specified). Default = FALSE.
digits	Rounding precision for reporting result.
plot	whether to plot the power.
silent	Suppress model runs printouts to console (TRUE)

Value

power table

References

• Miles, J. (2003). A framework for power analysis using a structural equation modelling procedure. BMC Medical Research Methodology, 3, 27. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1186/1471-2288-3-27")}

• Superpower package

See Also

• power.ACE.test(), umxRAM()

Other Teaching and Testing functions: tmx_show.MxModel(), umxDiagnose()

Examples

## Not run: 
# ===================================================
# = Power to detect correlation of .3 in 200 people =
# ===================================================

# 1 Make some data
tmp = umx_make_raw_from_cov(qm(1, .3| .3, 1), n=2000, varNames= c("X", "Y"), empirical= TRUE)

# 2. Make model of true XY correlation of .3
m1 = umxRAM("corXY", data = tmp,
   umxPath("X", with = "Y"),
   umxPath(var = c("X", "Y"))
)
# 3. Test power to detect .3 versus 0, with n= 90 subjects
umxPower(m1, "X_with_Y", n= 90)

# ####################
# # Estimating power #
# ####################
# 
#    method = ncp
#         n = 90
#     power = 0.83
# sig.level = 0.05
# statistic = LRT

# =================================================
# = Tabulate Power across a range of values of  n =
# =================================================
umxPower(m1, "X_with_Y", explore = TRUE)

# =====================================
# = Examples with method = empirical  =
# =====================================

# Power to detect r = .3 given n=90
umxPower(m1, "X_with_Y", n = 90, method = "empirical")
# power is .823
# Test using cor.test doing the same thing.
pwr::pwr.r.test(r = .3, n = 90)
#           n = 90
#           r = 0.3
#   sig.level = 0.05
#       power = 0.827
# alternative = two.sided

# Power search for detectable effect size, given n = 90
umxPower(m1, "X_with_Y", explore = TRUE)
umxPower(m1, "X_with_Y", n= 90, explore = TRUE)
umxPower(m1, "X_with_Y", n= 90, method = "empirical", explore = TRUE)


data(twinData) # ?twinData from Australian twins.
twinData[, c("ht1", "ht2")] = twinData[, c("ht1", "ht2")] * 10
mzData = twinData[twinData$zygosity %in% "MZFF", ]
dzData = twinData[twinData$zygosity %in% "DZFF", ]
m1 = umxACE(selDVs = "ht", selCovs = "age", sep = "", dzData = dzData, mzData = mzData)

# drop more than 1 path
umxPower(m1, update = c("c_r1c1", "age_b_Var1"), method = 'ncp', n=90, explore = TRUE)

# Specify only 1 parameter (not 'age_b_Var1' and 'c_r1c1' ) to search a parameter:power relationship
# note: Can't use method = "ncp" with search)
umxPower(m1, update = c("c_r1c1", "age_b_Var1"), method = 'empirical', n=90, explore = TRUE)
umxPower(m1, update = c("c_r1c1"), method = 'empirical', n=90, explore = TRUE)


## End(Not run)

umx documentation built on May 29, 2024, 5:40 a.m.