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Grilli, L. and Pratesi, M. (2004) Weighted Estimation in Multilevel Ordinal and Binary Models in the Presence of Informative Sampling Designs. Survey Methodology, 30, 93-104.

has been cited by the following article:

• TITLE: Multilevel Modeling of Binary Outcomes with Three-Level Complex Health Survey Data

  AUTHORS: Shafquat Rozi, Sadia Mahmud, Gillian Lancaster, Wilbur Hadden, Gregory Pappas

  KEYWORDS: Health Care Utilization, Complex Health Survey with Sampling Weights, Simulations for Complex Survey, Pseudo Likelihood, Three-Level Data

  JOURNAL NAME: Open Journal of Epidemiology, Vol.7 No.1, January 25, 2017

  ABSTRACT: Complex survey designs often involve unequal selection probabilities of clus-ters or units within clusters. When estimating models for complex survey data, scaled weights are incorporated into the likelihood, producing a pseudo likeli-hood. In a 3-level weighted analysis for a binary outcome, we implemented two methods for scaling the sampling weights in the National Health Survey of Pa-kistan (NHSP). For NHSP with health care utilization as a binary outcome we found age, gender, household (HH) goods, urban/rural status, community de-velopment index, province and marital status as significant predictors of health care utilization (p-value