Description Usage Arguments Details Value References Examples
delta_mean_item
computes the expected bias in item mean due to
measurement nonequivalence.
1 2 | delta_mean_item(LambdaR, ThreshR, LambdaF, ThreshF, MeanF, VarF,
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. |
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 6 of Nye & Drasgow (2011). Default value is .001.
A larger value can be used for faster performance; accuracy is
excellent at |
delta_mean_item
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 item mean due to measurement nonequivalence in equation 4 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.
1 2 3 4 5 6 7 | LambdaF <- 0.74
LambdaR <- 0.76
ThreshF <- 1.28
ThreshR <- 0.65
MeanF <- 0.21
VarF <- 1.76
delta_mean_item(LambdaR, ThreshR, LambdaF, ThreshF, MeanF, VarF)
|
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