delta_var {dmacs} | R Documentation |
delta_var
computes the expected bias in total score variance due
to measurement nonequivalence. delta_var
will only work for
unidimensional linear models (not categorical).
delta_var(LambdaR, LambdaF, VarF, categorical = FALSE)
LambdaR |
is the vector of factor loadings for the reference group. |
LambdaF |
is the vector of factor loadings for the focal group. |
VarF |
is the factor variance of the focal group. |
categorical |
is a Boolean variable declaring whether the variables in the model are ordered categorical. Categorical indicators are not supported for this function. |
delta_var
is called by dmacs_summary_single
, which
in turn is called by lavaan_dmacs
and
mplus_dmacs
, which are the only functions in this
package intended for casual users
The expected bias in total score variance due to measurement nonequivalence in equation 7, 8, and 9 of Nye & Drasgow (2011).
Nye, C. & Drasgow, F. (2011). Effect size indices for analyses of measurement equivalence: Understanding the practical importance of differences between groups. Journal of Applied Psychology, 96(5), 966-980.
LambdaF <- c(1.00, 0.74, 1.14, 0.92) LambdaR <- c(1.00, 0.76, 1.31, 0.98) VarF <- 1.76 delta_var(LambdaR, LambdaF, VarF)