### Abstract

We consider the question of how variation in the number and reliability of indicators affects the power to reject the hypothesis that the regression coefficients are zero in latent linear regression analysis. We show that power remains constant as long as the coefficient of determination remains unchanged. Any increase in the number of indicators always results in an increase in the coefficient of determination and so in the power. We note that the coefficient of determination plays a similar role in determining the error variance of predicted factor scores.

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

Pages (from-to) | 210-216 |

Number of pages | 7 |

Journal | Structural Equation Modeling |

Volume | 11 |

Issue number | 2 |

DOIs | |

State | Published - Jan 1 2004 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

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

### Cite this

}

*Structural Equation Modeling*, vol. 11, no. 2, pp. 210-216. https://doi.org/10.1207/s15328007sem1102_4

**A note on the relationship between the number of indicators and their reliability in detecting regression coefficients in latent regression analysis.** / Dolan, Conor V.; Wicherts, Jelte M.; Molenaar, Peter C.M.

Research output: Contribution to journal › Article

TY - JOUR

T1 - A note on the relationship between the number of indicators and their reliability in detecting regression coefficients in latent regression analysis

AU - Dolan, Conor V.

AU - Wicherts, Jelte M.

AU - Molenaar, Peter C.M.

PY - 2004/1/1

Y1 - 2004/1/1

N2 - We consider the question of how variation in the number and reliability of indicators affects the power to reject the hypothesis that the regression coefficients are zero in latent linear regression analysis. We show that power remains constant as long as the coefficient of determination remains unchanged. Any increase in the number of indicators always results in an increase in the coefficient of determination and so in the power. We note that the coefficient of determination plays a similar role in determining the error variance of predicted factor scores.

AB - We consider the question of how variation in the number and reliability of indicators affects the power to reject the hypothesis that the regression coefficients are zero in latent linear regression analysis. We show that power remains constant as long as the coefficient of determination remains unchanged. Any increase in the number of indicators always results in an increase in the coefficient of determination and so in the power. We note that the coefficient of determination plays a similar role in determining the error variance of predicted factor scores.

UR - http://www.scopus.com/inward/record.url?scp=2642533653&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=2642533653&partnerID=8YFLogxK

U2 - 10.1207/s15328007sem1102_4

DO - 10.1207/s15328007sem1102_4

M3 - Article

AN - SCOPUS:2642533653

VL - 11

SP - 210

EP - 216

JO - Structural Equation Modeling

JF - Structural Equation Modeling

SN - 1070-5511

IS - 2

ER -