24 citations · 28 across the 9 of their papers we have counts for
6 papers · 1 filter
Understanding the effects of dichotomization of continuous outcomes on geostatistical inference
Irene Kyomuhangi, Tarekegn A. Abeku, Matthew J. Kirby +2
Diagnosis is often based on the exceedance or not of continuous health indicators of a predefined cut-off value, so as to classify patients into positives and negatives for the dis…
A Geostatistical Framework for Combining Spatially Referenced Disease Prevalence Data from Multiple Diagnostics
Benjamin Amoah, Emanuele Giorgi, Peter Diggle
Multiple diagnostic tests are often used due to limited resources or because they provide complementary information on the epidemiology of a disease under investigation. Existing s…
Geostatistical inference in the presence of geomasking: a composite-likelihood approach
Claudio Fronterrè, Emanuele Giorgi, Peter J. Diggle
In almost any geostatistical analysis, one of the underlying, often implicit, modelling assump- tions is that the spatial locations, where measurements are taken, are recorded with…
Model-Based Geostatistics for Prevalence Mapping in Low-Resource Settings
Peter J. Diggle, Emanuele Giorgi
In low-resource settings, prevalence mapping relies on empirical prevalence data from a finite, often spatially sparse, set of surveys of communities within the region of interest,…
On The Inverse Geostatistical Problem of Inference on Missing Locations
Emanuele Giorgi, Peter J. Diggle
The standard geostatistical problem is to predict the values of a spatially continuous phenomenon, say, at locations using data where is the r…
Combining data from multiple spatially referenced prevalence surveys using generalized linear geostatistical models
Emanuele Giorgi, Sanie S. S. Sesay, Dianne J. Terlouw +1
Data from multiple prevalence surveys can provide information on common parameters of interest, which can therefore be estimated more precisely in a joint analysis than by separate…