ci.indirect {statpsych}R Documentation

Confidence interval for an indirect effect

Description

Computes a Monte Carlo confidence interval (500,000 trials) for a population unstandardized indirect effect in a path model. This function is not recommended for a standardized indirect effect unless the standardized slope estimates for both paths are less than about .3 in absolute value. The Monte Carlo method is general in that the slope estimates and standard errors do not need to be OLS estimates with homoscedastic standard errors. For example, LAD slope estimates and their standard errors, OLS slope estimates and heteroscedastic standard errors, distribution-free Theil-Sen slope estimates with McKean-Schrader standard errors, or standardized slopes with robust standard errors also could be used.

Usage

ci.indirect(alpha, b1, b2, se1, se2)

Arguments

alpha

alpha level for 1-alpha confidence

b1

unstandardized slope estimate for first path

b2

unstandardized slope estimate for second path

se1

standard error for b1

se2

standard error for b2

Value

Returns a 1-row matrix. The columns are:

Examples

ci.indirect (.05, 2.48, 1.92, .586, .379)

# Should return (within sampling error):
#      Estimate       SE       LL       UL
# [1,]   4.7616 1.625282 2.178812 7.972262
 


[Package statpsych version 1.3.0 Index]