## Abstract

In a regression setting, the partial correlation coefficient is often used as a measure of 'standardized' partial association between the outcome y and each of the covariates in x′ = [x_{1},..., x_{K} ]. In a linear regression model estimated using ordinary least squares, with y as the response, the estimated partial correlation coefficient between y and x_{k} can be shown to be a monotone function, denoted f(z), of the Z-statistic for testing if the regression coefficient of x_{k} is 0. When y is non-normal and the data are clustered so that y and x are obtained from each member of a cluster, generalized estimating equations are often used to estimate the regression parameters of the model for y given x. In this paper, when using generalized estimating equations, we propose using the above transformation f(z) of the GEE Z-statistic as a measure of partial association. Further, we also propose a coefficient of determination to measure the strength of association between the outcome variable and all of the covariates. To illustrate the method, we use a longitudinal study of the binary outcome heart toxicity from chemotherapy in children with leukaemia or sarcoma.

Original language | English (US) |
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Pages (from-to) | 175-190 |

Number of pages | 16 |

Journal | Statistical Modelling |

Volume | 7 |

Issue number | 2 |

DOIs | |

State | Published - Jul 2007 |

Externally published | Yes |

## Keywords

- Coefficient of determination
- Longitudinal data
- Repeated measures

## ASJC Scopus subject areas

- Statistics and Probability