METODE ROBUST GANDA DALAM MENANGANI PERANCU OLEH KLASTER; DOUBLY ROBUST METHODS FOR HANDLING CONFOUNDING BY CLUSTER

IHSANTI, ISMI NUR, Zulaela

2016 | Skripsi | FMIPA

In clustered designs, the exposure-outcome association is usually confounded by both cluster-constant and cluster-varying confounders. The influence of cluster-constant confounders can be eliminated by studying the exposure-outcome association within clusters using a regression model, but additional regression modeling is usually required to control for observed clustervarying confounders. A problem is that the working regression model may be misspecified, in which case the estimated within-cluster association may be biased. To reduce sensitivity model, there exist a new methods that augment the standard working model for the outcome with an auxiliary working model for the exposure. Then derive doubly robust conditional generalized estimating equation (DRCGEE) methods. This methods combines the two models in such a way that it is consistent if either model is correct, not necessarily both. Thus, the DRCGEE estimator gives the researcher two chances instead of only one to make valid inference on the within-cluster association.

Kata Kunci : clustered design, confounding, doubly robust methods