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P1-506 Multilevel modelling of survey data
  1. S Rozi1,2,
  2. S Mahmud1,
  3. G Lancaster2
  1. 1Aga Khan University, Karachi, Pakistan
  2. 2Lancaster University, Lancaster, UK

Abstract

Introduction Presently, about five million people worldwide die yearly from tobacco related diseases. The WHO currently estimates that there are 1.3 billion people who are regular smokers.

Objectives of data analysis To develop two level random effects logistic regression model for the analysis of clustered binary responses to identify factors associated with smoking among school going male adolescents. To assess if the variability between schools is different for the public and private schools using a random coefficient model. Two random effects will account for the variability between public and private schools respectively. To fit a contrasting Generalising Estimating Equation model to deal with two level clustered data for binary outcome. To compare and evaluate the results from the above mentioned models with a conventional logistic regression model as used in the original study.

Methods A two-stage cluster sampling with stratification based on school type was employed for the selection of schools and students. We interviewed 772 male secondary school students. The outcome variable is smoking status of the students. We have two level data with a single level of clustering.

Results Final multilevel random effect model showed that between cluster variance is significantly different from zero (p value of likelihood ratio test =0.01), which indicates that there is variability between schools and we need to take between cluster variation into account by using multilevel modelling. The Intra-class Correlation quantifies consistencies among observations within each cluster and it is also greater than zero (ICC =0.15).

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