Abstract
A latent variable modeling method for studying measurement invariance when evaluating latent constructs with multiple binary or binary scored items with no guessing is outlined. The approach extends the continuous indicator procedure described by Raykov and colleagues, utilizes similarly the false discovery rate approach to multiple testing, and permits one to locate violations of measurement invariance in loading or threshold parameters. The discussed method does not require selection of a reference observed variable and is directly applicable for studying differential item functioning with one- or two-parameter item response models. The extended procedure is illustrated on an empirical data set.
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