ci.indirect {statpsych} | R Documentation |
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.
ci.indirect(alpha, b1, b2, se1, se2)
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 |
Returns a 1-row matrix. The columns are:
Estimate - estimated indirect effect
SE - standard error of indirect effect
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
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