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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