Estimating the Intracluster Correlation Coefficient for the Clinical Sign “Trachomatous Inflammation—Follicular” in Population-Based Trachoma Prevalence Surveys: Results From a Meta-Regression Analysis of 261 Standardized Preintervention Surveys Carried Out in Ethiopia, Mozambique, and Nigeria

Abstract Sample sizes in cluster surveys must be greater than those in surveys using simple random sampling in order to obtain similarly precise prevalence estimates, because results from subjects examined in the same cluster cannot be assumed to be independent. Therefore, a crucial aspect of cluste...

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Veröffentlicht in:American journal of epidemiology 2020-01, Vol.189 (1), p.68-76
Hauptverfasser: Macleod, Colin K, Bailey, Robin L, Dejene, Michael, Shafi, Oumer, Kebede, Biruck, Negussu, Nebiyu, Mpyet, Caleb, Olobio, Nicholas, Alada, Joel, Abdala, Mariamo, Willis, Rebecca, Hayes, Richard, Solomon, Anthony W
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container_title American journal of epidemiology
container_volume 189
creator Macleod, Colin K
Bailey, Robin L
Dejene, Michael
Shafi, Oumer
Kebede, Biruck
Negussu, Nebiyu
Mpyet, Caleb
Olobio, Nicholas
Alada, Joel
Abdala, Mariamo
Willis, Rebecca
Hayes, Richard
Solomon, Anthony W
description Abstract Sample sizes in cluster surveys must be greater than those in surveys using simple random sampling in order to obtain similarly precise prevalence estimates, because results from subjects examined in the same cluster cannot be assumed to be independent. Therefore, a crucial aspect of cluster sampling is estimation of the intracluster correlation coefficient (ρ): the degree of relatedness of outcomes in a given cluster, defined as the proportion of total variance accounted for by between-cluster variation. In infectious disease epidemiology, this coefficient is related to transmission patterns and the natural history of infection; its value also depends on particulars of survey design. Estimation of ρ is often difficult due to the lack of comparable survey data with which to calculate summary estimates. Here we use a parametric bootstrap model to estimate ρ for the ocular clinical sign “trachomatous inflammation—follicular” (TF) among children aged 1–9 years within population-based trachoma prevalence surveys. We present results from a meta-regression analysis of data from 261 such surveys completed using standardized methods in Ethiopia, Mozambique, and Nigeria in 2012–2015. Consistent with the underlying theory, we found that ρ increased with increasing overall TF prevalence and smaller numbers of children examined per cluster. Estimates of ρ for TF were independently higher in Ethiopia than in the other countries.
doi_str_mv 10.1093/aje/kwz196
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surveys</topic><topic>Practice of Epidemiology</topic><topic>Prevalence</topic><topic>Random sampling</topic><topic>Regression Analysis</topic><topic>Sampling</topic><topic>Statistical sampling</topic><topic>Trachoma</topic><topic>Trachoma - epidemiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Macleod, Colin K</creatorcontrib><creatorcontrib>Bailey, Robin L</creatorcontrib><creatorcontrib>Dejene, Michael</creatorcontrib><creatorcontrib>Shafi, Oumer</creatorcontrib><creatorcontrib>Kebede, Biruck</creatorcontrib><creatorcontrib>Negussu, Nebiyu</creatorcontrib><creatorcontrib>Mpyet, Caleb</creatorcontrib><creatorcontrib>Olobio, Nicholas</creatorcontrib><creatorcontrib>Alada, Joel</creatorcontrib><creatorcontrib>Abdala, Mariamo</creatorcontrib><creatorcontrib>Willis, Rebecca</creatorcontrib><creatorcontrib>Hayes, Richard</creatorcontrib><creatorcontrib>Solomon, Anthony W</creatorcontrib><collection>Oxford Journals Open Access Collection</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium &amp; 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Therefore, a crucial aspect of cluster sampling is estimation of the intracluster correlation coefficient (ρ): the degree of relatedness of outcomes in a given cluster, defined as the proportion of total variance accounted for by between-cluster variation. In infectious disease epidemiology, this coefficient is related to transmission patterns and the natural history of infection; its value also depends on particulars of survey design. Estimation of ρ is often difficult due to the lack of comparable survey data with which to calculate summary estimates. Here we use a parametric bootstrap model to estimate ρ for the ocular clinical sign “trachomatous inflammation—follicular” (TF) among children aged 1–9 years within population-based trachoma prevalence surveys. We present results from a meta-regression analysis of data from 261 such surveys completed using standardized methods in Ethiopia, Mozambique, and Nigeria in 2012–2015. 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source Oxford University Press Journals All Titles (1996-Current); MEDLINE; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection
subjects Child
Child, Preschool
Children
Cluster Analysis
Clusters
Coefficient of variation
Correlation coefficient
Correlation coefficients
Correlation of Data
Cross-Sectional Studies
Epidemiology
Estimates
Ethiopia - epidemiology
Female
Humans
Infant
Infectious diseases
Inflammation
Male
Mathematical analysis
Mozambique - epidemiology
Nigeria - epidemiology
Polls & surveys
Practice of Epidemiology
Prevalence
Random sampling
Regression Analysis
Sampling
Statistical sampling
Trachoma
Trachoma - epidemiology
title Estimating the Intracluster Correlation Coefficient for the Clinical Sign “Trachomatous Inflammation—Follicular” in Population-Based Trachoma Prevalence Surveys: Results From a Meta-Regression Analysis of 261 Standardized Preintervention Surveys Carried Out in Ethiopia, Mozambique, and Nigeria
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