calculateHTMT {cSEM} | R Documentation |

Computes either the heterotrait-monotrait ratio of correlations (HTMT) based on Henseler et al. (2015) or its advancement HTMT2. While the HTMT is a consistent estimator for the construct correlation in case of tau-equivalent measurement models, the HTMT2 is a consistent estimator for congeneric measurement models. In general, they are used to assess discriminant validity.

calculateHTMT( .object = NULL, .type_htmt = c('htmt','htmt2'), .absolute = TRUE, .alpha = 0.05, .ci = c("CI_percentile", "CI_standard_z", "CI_standard_t", "CI_basic", "CI_bc", "CI_bca", "CI_t_interval"), .handle_inadmissibles = c("drop", "ignore", "replace"), .inference = FALSE, .only_common_factors = TRUE, .R = 499, .seed = NULL, ... )

`.object` |
An R object of class cSEMResults resulting from a call to |

`.type_htmt` |
Character string indicating the type of HTMT that should be
calculated, i.e., the original HTMT (" |

`.absolute` |
Logical. Should the absolute HTMT values be returned?
Defaults to |

`.alpha` |
A numeric value giving the significance level.
Defaults to |

`.ci` |
A character strings naming the type of confidence interval to use
to compute the 1-alpha% quantile of the bootstrap HTMT values. For possible
choices see |

`.handle_inadmissibles` |
Character string. How should inadmissible results
be treated? One of " |

`.inference` |
Logical. Should critical values be computed? Defaults to |

`.only_common_factors` |
Logical. Should only concepts modeled as common
factors be included when calculating one of the following quality critera:
AVE, the Fornell-Larcker criterion, HTMT, and all reliability estimates.
Defaults to |

`.R` |
Integer. The number of bootstrap replications. Defaults to |

`.seed` |
Integer or |

`...` |
Ignored. |

Computation of the HTMT assumes that all intra-block and inter-block
correlations between indicators are either all-positive or all-negative.
A warning is given if this is not the case. If all intra-block or inter-block
correlations are negative the absolute HTMT values are returned (`.absolute = TRUE`

).

To obtain the 1-alpha%-quantile of the bootstrap distribution for each HTMT
value set `.inference = TRUE`

. To choose the type of confidence interval to use
to compute the 1-alpha%-quantile, use `.ci`

. To control the bootstrap process,
arguments `.handle_inadmissibles`

, `.R`

and `.seed`

are available.

Since the HTMT is defined with respect to a classical true score measurement
model only concepts modeled as common factors are considered by default.
For concepts modeled as composites the HTMT may be computed by setting
`.only_common_factors = FALSE`

, however, it is unclear how to
interpret values in this case.

A lower tringular matrix of HTMT values. If `.inference = TRUE`

the upper tringular part is the 1-.alpha%-quantile of the HTMT's bootstrap
distribution.

Henseler J, Ringle CM, Sarstedt M (2015).
“A New Criterion for Assessing Discriminant Validity in Variance-based Structural Equation Modeling.”
*Journal of the Academy of Marketing Science*, **43**(1), 115–135.
doi: 10.1007/s11747-014-0403-8, https://doi.org/10.1007/s11747-014-0403-8.

[Package *cSEM* version 0.4.0 Index]