## Abstract

Often problems result in the collection of coupled data, which consist of different N-way N-mode data blocks that have one or more modes in common. To reveal the structure underlying such data, an integrated modeling strategy, with a single set of parameters for the common mode(s), that is estimated based on the information in all data blocks, may be most appropriate. Such a strategy implies a global model, consisting of different N-way N-mode submodels, and a global loss function that is a (weighted) sum of the partial loss functions associated with the different submodels. In this paper, such a global model for an integrated analysis of a three-way three-mode binary data array and a two-way two-mode binary data matrix that have one mode in common is presented. A simulated annealing algorithm to estimate the model parameters is described and evaluated in a simulation study. An application of the model to real psychological data is discussed.

Original language | English |
---|---|

Pages (from-to) | 729-751 |

Number of pages | 23 |

Journal | Psychometrika |

Volume | 73 |

Issue number | 4 |

DOIs | |

Publication status | Published - 1 Dec 2008 |

Externally published | Yes |

## Keywords

- Binary data
- Clustering
- Coupled data
- Data fusion
- Hierarchical classes
- Multi-way data analysis
- Three-way three-mode data