item_dmacs {dmacs} | R Documentation |
item_dmacs
computes the dmacs effect size for a single indicator
relative to a single factor in a single focal group
item_dmacs(LambdaR, ThreshR, LambdaF, ThreshF, MeanF, VarF, SD, categorical = FALSE, stepsize = 0.001)
LambdaR |
is the factor loading of the item onto the factor of interest for the reference group. |
ThreshR |
is the indicator intercept (for continuous indicators) or a vector of thresholds (for categorical indicators) for the reference group. |
LambdaF |
is the factor loading of the item onto the factor of interest for the focal group. |
ThreshF |
is the indicator intercept (for continuous indicators) or a vector of thresholds (for categorical indicators) for the focal group. |
MeanF |
is the factor mean in the focal group |
VarF |
is the factor variances in the focal group. |
SD |
is the indicator standard deviations to be used as the denominator of the dmacs effect size. This will usually either be pooled standard deviation for the indicator or the standard deviation for the indicator in the reference group. |
categorical |
is a Boolean variable declaring whether the variables
in the model are ordered categorical. Models in which some variables are
categorical and others are continuous are not supported. If no value is
provided, categorical defaults to |
stepsize |
is the interval width for the Riemann sum used to estimate
the integral in equation 3 of Nye & Drasgow (2011). Default value is .001.
A larger value can be used for faster performance; accuracy is
excellent at |
item_dmacs
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 dmacs effect size of equation 3 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 <- 0.74 LambdaR <- 0.76 ThreshF <- 1.28 ThreshR <- 0.65 MeanF <- 0.21 VarF <- 1.76 SD <- 1.85 item_dmacs(LambdaR, ThreshR, LambdaF, ThreshF, MeanF, VarF, SD)