### Abstract

Some nonlinear developmental phenomena can be represented by using a simple piecewise procedure in which 2 linear growth models are joined at a single knot. The major problem of using this piecewise approach is that researchers have to optimally locate the knot (or turning point) where the change in the growth rate occurs. A relatively simple way to detect the location of the knot or turning point is to freely estimate the time-specific factor loadings using the linear latent growth model framework. The major goal of this simulation study was to examine the effectiveness of using modification indexes (MIs) to detect potential turning points in longitudinal data. The results showed that when using a restricted search strategy with an adequate number of both observations (210) and measurement waves (8), MIs performed well in detecting a medium change in the growth rate between two linear models at the turning point. Implications of the findings and limitations are discussed.

Original language | English (US) |
---|---|

Pages (from-to) | 216-240 |

Number of pages | 25 |

Journal | Structural Equation Modeling |

Volume | 17 |

Issue number | 2 |

DOIs | |

State | Published - Apr 2010 |

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### ASJC Scopus subject areas

- Modeling and Simulation
- Decision Sciences(all)
- Economics, Econometrics and Finance(all)
- Sociology and Political Science

### Cite this

*Structural Equation Modeling*,

*17*(2), 216-240. https://doi.org/10.1080/10705511003659359

**Using modification indexes to detect turning points in longitudinal data : A monte Carlo study.** / Kwok, Oi Man; Luo, Wen; West, Stephen.

Research output: Contribution to journal › Article

*Structural Equation Modeling*, vol. 17, no. 2, pp. 216-240. https://doi.org/10.1080/10705511003659359

}

TY - JOUR

T1 - Using modification indexes to detect turning points in longitudinal data

T2 - A monte Carlo study

AU - Kwok, Oi Man

AU - Luo, Wen

AU - West, Stephen

PY - 2010/4

Y1 - 2010/4

N2 - Some nonlinear developmental phenomena can be represented by using a simple piecewise procedure in which 2 linear growth models are joined at a single knot. The major problem of using this piecewise approach is that researchers have to optimally locate the knot (or turning point) where the change in the growth rate occurs. A relatively simple way to detect the location of the knot or turning point is to freely estimate the time-specific factor loadings using the linear latent growth model framework. The major goal of this simulation study was to examine the effectiveness of using modification indexes (MIs) to detect potential turning points in longitudinal data. The results showed that when using a restricted search strategy with an adequate number of both observations (210) and measurement waves (8), MIs performed well in detecting a medium change in the growth rate between two linear models at the turning point. Implications of the findings and limitations are discussed.

AB - Some nonlinear developmental phenomena can be represented by using a simple piecewise procedure in which 2 linear growth models are joined at a single knot. The major problem of using this piecewise approach is that researchers have to optimally locate the knot (or turning point) where the change in the growth rate occurs. A relatively simple way to detect the location of the knot or turning point is to freely estimate the time-specific factor loadings using the linear latent growth model framework. The major goal of this simulation study was to examine the effectiveness of using modification indexes (MIs) to detect potential turning points in longitudinal data. The results showed that when using a restricted search strategy with an adequate number of both observations (210) and measurement waves (8), MIs performed well in detecting a medium change in the growth rate between two linear models at the turning point. Implications of the findings and limitations are discussed.

UR - http://www.scopus.com/inward/record.url?scp=77951665183&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77951665183&partnerID=8YFLogxK

U2 - 10.1080/10705511003659359

DO - 10.1080/10705511003659359

M3 - Article

AN - SCOPUS:77951665183

VL - 17

SP - 216

EP - 240

JO - Structural Equation Modeling

JF - Structural Equation Modeling

SN - 1070-5511

IS - 2

ER -