We propose a new method for analyzing longitudinal data which contain responses
that are missing at random. This method consists in solving the generalized estimating
equation (GEE) of [7] in which the incomplete responses are replaced by values
adjusted using the inverse probability weights proposed in [14]. We show that the
root estimator is consistent and asymptotically normal, essentially under some conditions on the marginal distribution and the surrogate correlation matrix as those
presented in [12] in the case of complete data, and under minimal assumptions on
the missingness probabilities. This method is applied to a real-life dataset taken from
[10], which examines the incidence of respiratory disease in a sample of 250 pre-school age Indonesian children which were examined every 3 months for 18 months, using as covariates the age, gender, and vitamin A deficiency.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/37838 |
| Date | 11 July 2018 |
| Creators | Jankovic, Dina |
| Contributors | Balan, Raluca Madalina |
| Publisher | Université d'Ottawa / University of Ottawa |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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