TY - JOUR

T1 - A measure of partial association for generalized estimating equations

AU - Natarajan, Sundar

AU - Lipsitz, Stuart

AU - Parzen, Michael

AU - Lipshultz, Stephen

N1 - Copyright:
Copyright 2007 Elsevier B.V., All rights reserved.

PY - 2007/7

Y1 - 2007/7

N2 - 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′ = [x1,..., xK ]. In a linear regression model estimated using ordinary least squares, with y as the response, the estimated partial correlation coefficient between y and xk can be shown to be a monotone function, denoted f(z), of the Z-statistic for testing if the regression coefficient of xk 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.

AB - 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′ = [x1,..., xK ]. In a linear regression model estimated using ordinary least squares, with y as the response, the estimated partial correlation coefficient between y and xk can be shown to be a monotone function, denoted f(z), of the Z-statistic for testing if the regression coefficient of xk 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.

KW - Coefficient of determination

KW - Longitudinal data

KW - Repeated measures

UR - http://www.scopus.com/inward/record.url?scp=34848919464&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34848919464&partnerID=8YFLogxK

U2 - 10.1177/1471082X0700700204

DO - 10.1177/1471082X0700700204

M3 - Article

AN - SCOPUS:34848919464

VL - 7

SP - 175

EP - 190

JO - Statistical Modelling

JF - Statistical Modelling

SN - 1471-082X

IS - 2

ER -