### Abstract

In many epidemiologic data, the dose-response relation between a continuous exposure and the risk of disease abruptly changes when the exposure variable reaches an unknown threshold level, the so-called change- point. Although several methods are available for dose-response assessment with dichotomous outcomes, none of them provide inferential procedures to estimate change-points. In this paper, we describe a two-segmented logistic regression model, in which the linear term associated with a continuous exposure in standard logistic regression is replaced by a two-segmented polynomial function with unknown change-point, which is also estimated. A modified, iteratively reweighted least squares algorithm is presented to obtain parameter estimates and confidence intervals, and the performance of this model is explored through simulation. Finally, a two-segmented logistic regression model is applied to a case-control study of the association of alcohol intake with the risk of myocardial infarction and compared with alternative analyses. The ability of two-segmented logistic regression to estimate and provide inferences for the location of change-points and for the magnitude of other parameters of effect will make this model a useful complement to other methods of dose-response analysis in epidemiologic studies.

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

Pages (from-to) | 631-642 |

Number of pages | 12 |

Journal | American Journal of Epidemiology |

Volume | 148 |

Issue number | 7 |

State | Published - Oct 1 1998 |

Externally published | Yes |

### Fingerprint

### Keywords

- Case-control studies
- Epidemiologic methods
- Logistic models
- Risk assessment

### ASJC Scopus subject areas

- Epidemiology

### Cite this

*American Journal of Epidemiology*,

*148*(7), 631-642.

**Use of two-segmented logistic regression to estimate change-points in epidemiologic studies.** / Pastor, Roberto; Guallar, Eliseo.

Research output: Contribution to journal › Article

*American Journal of Epidemiology*, vol. 148, no. 7, pp. 631-642.

}

TY - JOUR

T1 - Use of two-segmented logistic regression to estimate change-points in epidemiologic studies

AU - Pastor, Roberto

AU - Guallar, Eliseo

PY - 1998/10/1

Y1 - 1998/10/1

N2 - In many epidemiologic data, the dose-response relation between a continuous exposure and the risk of disease abruptly changes when the exposure variable reaches an unknown threshold level, the so-called change- point. Although several methods are available for dose-response assessment with dichotomous outcomes, none of them provide inferential procedures to estimate change-points. In this paper, we describe a two-segmented logistic regression model, in which the linear term associated with a continuous exposure in standard logistic regression is replaced by a two-segmented polynomial function with unknown change-point, which is also estimated. A modified, iteratively reweighted least squares algorithm is presented to obtain parameter estimates and confidence intervals, and the performance of this model is explored through simulation. Finally, a two-segmented logistic regression model is applied to a case-control study of the association of alcohol intake with the risk of myocardial infarction and compared with alternative analyses. The ability of two-segmented logistic regression to estimate and provide inferences for the location of change-points and for the magnitude of other parameters of effect will make this model a useful complement to other methods of dose-response analysis in epidemiologic studies.

AB - In many epidemiologic data, the dose-response relation between a continuous exposure and the risk of disease abruptly changes when the exposure variable reaches an unknown threshold level, the so-called change- point. Although several methods are available for dose-response assessment with dichotomous outcomes, none of them provide inferential procedures to estimate change-points. In this paper, we describe a two-segmented logistic regression model, in which the linear term associated with a continuous exposure in standard logistic regression is replaced by a two-segmented polynomial function with unknown change-point, which is also estimated. A modified, iteratively reweighted least squares algorithm is presented to obtain parameter estimates and confidence intervals, and the performance of this model is explored through simulation. Finally, a two-segmented logistic regression model is applied to a case-control study of the association of alcohol intake with the risk of myocardial infarction and compared with alternative analyses. The ability of two-segmented logistic regression to estimate and provide inferences for the location of change-points and for the magnitude of other parameters of effect will make this model a useful complement to other methods of dose-response analysis in epidemiologic studies.

KW - Case-control studies

KW - Epidemiologic methods

KW - Logistic models

KW - Risk assessment

UR - http://www.scopus.com/inward/record.url?scp=0032191938&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032191938&partnerID=8YFLogxK

M3 - Article

VL - 148

SP - 631

EP - 642

JO - American Journal of Epidemiology

JF - American Journal of Epidemiology

SN - 0002-9262

IS - 7

ER -