dmacs_summary: Summary of measurement nonequivalence effects
In dmacs: Measurement Nonequivalence Effect Size Calculator

Description Usage Arguments Details Value References Examples

dmacs_summary returns a summary of measurement non-equivalence effects given lists of parameters.

1 2	dmacs_summary(LambdaList, ThreshList, MeanList, VarList, SDList, Groups = NULL, RefGroup = 1, categorical = FALSE, ...)

`LambdaList`	is a list, indexed by groups, of factor loading matrices (dataframes are allowed).
`ThreshList`	is a list, indexed by groups, of vectors of indicator intercepts (for continuous indicators) or lists, indexed by items, of vectors of thresholds (for categorical indicators). For categorical indicators, do not provide a matrix of thresholds for each group.
`MeanList`	is a list, indexed by groups, of vectors of factor means. For unidimensional models, this is simply a list of factor means.
`VarList`	is a list, indexed by groups, of vectors of factor variances. For unidimensional models, this is simply a list of factor variances.
`SDList`	is a list, indexed by groups, of vectors of indicator observed standard deviations used as the denominator of the dmacs effect size. This will usually either be pooled standard deviations or the standard deviation of the reference group. Each group, including the reference group, must be included in SDList (although the standard deviations for the reference group are ignored).
`Groups`	is a vector of group names. If no value is provided, dmacs_summary will try to use `names(LambdaList)`; if LambdaList has no names, then the groups will be numbered.
`RefGroup`	can be the name of the reference group (as a string), or the index of the reference group (as a number). RefGroup defaults to the first group if no value is provided. It is strongly recommended to provide the reference group as a string, since group names in data are often ordered by their appearance in the data, not alphabetically.
`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 `FALSE`, although if multiple thresholds are provided for an item, categorical will be forced to `TRUE`. A graded response model with probit link (e.g., DWLS in lavaan or WLSMV in Mplus) is used for categorical variables. If you desire for other categorical models (e.g., IRT parameterization) to be supported, e-mail the maintainer.
`...`	other parameters to be used in functions that `dmacs_summary` calls, most likely `stepsize` for the `item_dmacs` and `delta_mean_item` functions.

dmacs_summary is called by lavaan_dmacs and mplus_dmacs, which are the only functions in this package intended for casual users

A list, indexed by groups, of lists of measurement nonequivalence effects from Nye and Drasgow (2011), including dmacs, expected bias in the mean score by item, expected bias in the mean total score, and expected bias in the variance of the total score. Expected bias in the variance of the total score is only supplied for unidimensional models with linear indicators (i.e., not categorical) in the current version of this package.

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.

LambdaList <- list(Group1 <- matrix(c(1.00, 0.74,  1.14, 0.92), ncol = 1),
                   Group2 <- matrix(c(1.00, 0.76,  1.31, 0.98), ncol = 1))
ThreshList <- list(Group1 <- c(0.00, 1.28, -0.82, 0.44),
                   Group2 <- c(0.00, 0.65, -0.77, 0.47))
MeanList   <- list(Group1 <- 0.21,
                   Group2 <- 0.19)
VarList    <- list(Group1 <- 1.76,
                   Group2 <- 1.34)
SDList     <- list(Group1 <- c(2.12, 1.85,  1.12, 3.61),
                   Group2 <- c(NA, NA, NA, NA))
Groups <- c("Group1", "Group2")
RefGroup <- "Group2"
dmacs_summary(LambdaList, ThreshList, MeanList, VarList, SDList,
              Groups, RefGroup)