Adjusting for selective attrition in a longitudinal study assessing the rate of cognitive decline Pubblico

Abstract

The thesis aimed to adjust for selective attrition in a longitudinal study that examined the rate of cognitive decline. It used longitudinal data from the Uniform Data Set of the National Alzheimer's Coordinating Center and conducted the analyses on 32,502 participants who were diagnosed as either cognitively normal, mildly cognitively impaired, or demented at the initial visit. The study used two methods, the inverse probability of attrition weighting (IPAW) method and multiple imputations, to investigate the effect of attrition-related selection bias on the estimated association between various factors and cognitive decline. IPAW approach allows for the use of all available data, assuming accurate estimation of attrition probability, and in this specific dataset, it may be preferable to use IPAW rather than imputation. However, the choice of method will depend on the specific characteristics of the dataset and assumptions about attrition.

Table of Contents

1 Introduction 1

2 Methods 3

2.1 Study data and population . . . . . . . . . . . . . . . . . . . . . . . . 3

2.2 Analytic Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2.2.1 Inverse probability of attrition weighting (IPAW) . . . . . . . 4

2.2.2 Generalized estimating equation (GEE) . . . . . . . . . . . . . 6

2.2.3 Multiple imputations . . . . . . . . . . . . . . . . . . . . . . . 6

3 Results 8

4 Discussion 12

Bibliography 14

About this Master's Thesis

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• Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.

School	Rollins School of Public Health
Department	Biostatistics
Subfield / Discipline	Biostatistics - MPH & MSPH
Degree	M.S.P.H.
Submission	Master's Thesis
Language	English
Research Field	Biology, Biostatistics
Parola chiave	Multiple imputation selective attrition IPAW longitudinal data
Committee Chair / Thesis Advisor	John Hanfelt, Emory University

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