Enter your Email address:
Wolters Kluwer Health may email you for journal alerts and information, but is committed
to maintaining your privacy and will not share your personal information without
You currently have no recent searches
Barnett, Adrian*; Williams, Gail*; Neller, Anne†; Best, Trudi†; Simpson, Rod†
*The University of Queensland; †University of the Sunshine Coast
Polynomial Distributed Lag (PDL) models are a useful method for studying the long-term effects of air pollution exposure on morbidity and mortality. The model assumes that the past effects of air pollution (in days) vary smoothly according to a parametric polynomial shape. The model's key parameters are the order of the polynomial and the number of past days (P); both of which are ideally chosen to give an optimal fit to the data. In making this optimal selection two problems occur: 1) increasing the number of past days (P) does not add extra terms to the Akaike Information Criteria (AIC), and so it cannot be used to assess the optimal value of P; 2) the polynomial assumption means that very non-linear patterns require a high order model. In this paper, we tackled these problems by fitting a non-parametric window to a set of unconstrained lagged covariates, and used the Deviance Information Criteria (DIC) to select the optimal value of P.
We smoothed a set unconstrained lagged covariates β to β[P], using a moving average (MA): β[i]*=(β[i−1]+ β[i]+β[i+1])/3, i=2,. . .P−1; β*=β; β[P]*=β[P]. The order of the PDL model was chosen by testing the orthogonal polynomial estimates. We compared the performance of the methods using a simulation study of a non-linear time-varying effect.
In the simulation study a PDL model of order six captured the non-linear pattern well (Figure 1); the area under the curve was estimated as 18.7 (95% Confidence Interval: 17.3, 20.0) compared to the true value of 17.5. The DIC performed well as an indicator of the correct value of P, whereas the AIC monotonically decreased with P (Figure 2.)
In our simulation study the DIC proved a useful statistic for choosing the crucial parameter of the number of past days in a distributed lag model. The PDL model gave estimates that were closer to the true effect compared those from a MA model which were comparatively noisy. We recommend combining the methods to give optimal estimates of long-term pollution effects.
© 2004 Lippincott Williams & Wilkins, Inc.
Colleague's E-mail is Invalid
Your Name: (optional)
Separate multiple e-mails with a (;).
Thought you might appreciate this item(s) I saw at Epidemiology.
Send a copy to your email
Your message has been successfully sent to your colleague.
Some error has occurred while processing your request. Please try after some time.
An Existing Folder
A New Folder
The item(s) has been successfully added to "".
Login with your LWW Journals username and password.
Username or Email:
Enter and submit the email address you registered with. An email with instructions to reset your password will be sent to that address.
Link to reset your password has been sent to specified email address.
What does "Remember me" mean?
By checking this box, you'll stay logged in until you logout. You'll get easier access to your articles, collections,
media, and all your other content, even if you close your browser or shut down your
To protect your most sensitive data and activities (like changing your password),
we'll ask you to re-enter your password when you access these services.
What if I'm on a computer that I share with others?
If you're using a public computer or you share this computer with others, we recommend
that you uncheck the "Remember me" box.
Save my selection
Article Level Metrics