The Houdini Transformation
True, but Illusory
Bibliographic Data
| ID | 19290777 |
|---|---|
| Authors | Peter M Bentler (0000-0002-9440-721X, University of California, Los Angeles), Peter C M Molenaar (0000-0002-0026-0756, Pennsylvania State University) |
| Year | 2012 |
| Volume | 47 |
| Issue | 3 |
| Pages | 442-447 |
| Publication date | 2012-06-18 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Multivariate Behavioral Research (JOURNAL) |
| Journal identifiers | ISSN: 0027-3171 • E-ISSN: 1532-7906 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00273171.2012.673941 |
| PMID | 23180888 |
| PMCID | PMC3501748 |
| OpenAlex | W1971371431 |
| Language | EN |
| Citations received | 3 |
| References cited | 7 |
Molenaar (2003, 2011) showed that a common factor model could be transformed into an equivalent model without factors, involving only observed variables and residual errors. He called this invertible transformation the Houdini transformation. His derivation involved concepts from time series and state space theory. This paper verifies the Houdini transformation on a general latent variable model using algebraic methods. The results show that the Houdini transformation is illusory, in the sense that the Houdini transformed model remains a latent variable model. Contrary to common knowledge, a model that is a path model with only observed variables and residual errors may, in fact, be a latent variable model
Algorithm · Arithmetic · Invertible matrix · Latent variable · Latent variable model · Path (computing) · Programming language · Pure mathematics · Residual · Series (stratigraphy) · Statistics · Transformation (genetics) · Variable (mathematics) · Advanced Text Analysis Techniques · Artificial Intelligence · Bayesian Modeling and Causal Inference · Computer Science · Mathematics
| Citations per year | 0.33 |
|---|---|
| Citation span | 2017 - 2024 (8) |
| Highly cited | No |