simsem (version 0.2-8)

findPower: Find a value of independent variables that provides a given value of power.

Description

Find a value of independent variable that provides a given value of power. If there are more than one varying parameters, this function will find the value of the target varying parameters given the values of the other varying parameters.

Usage

findPower(powerTable, iv, power)

Arguments

powerTable

A data.frame providing varying parameters and powers of each parameter. This table is obtained by getPower or continuousPower function.

iv

The target varying parameter that users would like to find the value providing a given power from. This argument can be specified as the index of the target column or the name of target column (i.e., "iv.N" or "N")

power

A desired power.

Value

• There are five possible types of values provided:
  • ValueThe varying parameter value that provides the power just over the specified power value (the adjacent value of varying parameter provides lower power than the specified power value).
  • Minimum valueThe minimum value has already provided enough power (way over the specified power value). The value of varying parameters that provides exact desired power may be lower than the minimum value. The example of varying parmaeter that can provides the minimum value is sample size.
  • Maximum valueThe maximum value has already provided enough power (way over the specified power value). The value of varying parameters that provides exact desired power may be higher than the maximum value. The example of varying parmaeter that can provides the maximum value is percent missing.
  • NAThere is no value in the domain of varying parameters that provides the power greater than the desired power.
  • NaNThe power of all values in the varying parameters is 1 (specifically more than 0.9999) and any values of the varying parameters can be picked and still provide enough power.

See Also

• getPowerto find the power of parameter estimates
• continuousPowerto find the power of parameter estimates for the result object (linkS4class{SimResult}) with varying parameters.

Examples

# Specify Sample Size by n
loading <- matrix(0, 6, 1)
loading[1:6, 1] <- NA
LX <- simMatrix(loading, 0.4)
RPH <- symMatrix(diag(1))
RTD <- symMatrix(diag(6))
CFA.Model <- simSetCFA(LY = LX, RPS = RPH, RTE = RTD)
SimData <- simData(CFA.Model, 500)
SimModel <- simModel(CFA.Model)

# Specify both sample size and percent missing completely at random
Output <- simResult(NULL, SimData, SimModel, n=seq(100, 200, 20), pmMCAR=c(0, 0.1, 0.2))
pow <- getPower(Output)
findPower(pow, "N", 0.80)