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- Auxillary variables; Biased sampling schemes; Ecological fallacy; Hiearchical models (1)
- Bayesian Methods; Ecological Bias; Ecological Correlation Studies; Hierarchical Models; Prior Distributions; Spatial Epidemiology; Standardization. (1)
- Empirical/statistical models; analytical methods; epidemiology; particulate matter; criteria pollutants (1)
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Prevalensi Dan Determinan Hipertensi Di Pulau Jawa, Tahun 2004, Zamhir Setiawan
Prevalensi Dan Determinan Hipertensi Di Pulau Jawa, Tahun 2004, Zamhir Setiawan
Kesmas
Hipertensi merupakan faktor risiko utama kardiovaskuler yang merupakan penyebab utama kematian di seluruh dunia. Peningkatan umur harapan hidup dan perubahan gaya hidup meningkatkan faktor risiko hipertensi di berbagai negara. Tujuan penelitian ini (1) Mengetahui prevalensi hipertensi dan penyebarannya di Pulau Jawa tahun 2004. (2) Mengetahui faktor-faktor sosiodemografi yang berhubungan dengan kejadian hipertensi. (3) Mengetahui kontribusi dan dampak potensial masing masing faktor tersebut. Penelitian dengan rancangan studi Ekologi Multilevel ini menggabungkan variabel tingkat pengukuran individu dengan tingkat pengukuran ekologi dalam analisis bersama, dengan unit analisis individu. Analisis kontekstual dilakukan melalui kerangka konsep hipertensi, menggunakan metode analisis regresi logistik ganda, dengan status …
Statistical Analysis Of Air Pollution Panel Studies: An Illustration, Holly Janes, Lianne Sheppard, Kristen Shepherd
Statistical Analysis Of Air Pollution Panel Studies: An Illustration, Holly Janes, Lianne Sheppard, Kristen Shepherd
UW Biostatistics Working Paper Series
The panel study design is commonly used to evaluate the short-term health effects of air pollution. Standard statistical methods for analyzing longitudinal data are available, but the literature reveals that the techniques are not well understood by practitioners. We illustrate these methods using data from the 1999 to 2002 Seattle panel study. Marginal, conditional, and transitional approaches for modeling longitudinal data are reviewed and contrasted with respect to their parameter interpretation and methods for accounting for correlation and dealing with missing data. We also discuss and illustrate techniques for controlling for time-dependent and time-independent confounding, and for exploring and summarizing …
Hierarchical Models For Combining Ecological And Case-Control Data, Sebastien Haneuse, Jon Wakefield
Hierarchical Models For Combining Ecological And Case-Control Data, Sebastien Haneuse, Jon Wakefield
UW Biostatistics Working Paper Series
The ecological study design suffers from a broad range of biases that result from the loss of information regarding the joint distribution of individual-level outcomes, exposures and confounders. The consequent non-identifiability of individual-level models cannot be overcome without additional information; we combine ecological data with a sample of individual-level case-control data. The focus of this paper is hierarchical models to account for between-group heterogeneity. Estimation and inference pose serious compu- tational challenges. We present a Bayesian implementation, based on a data augmentation scheme where the unobserved data are treated as auxiliary variables. The methods are illustrated with a dataset of …
Disease Mapping And Spatial Regression With Count Data, Jon Wakefield
Disease Mapping And Spatial Regression With Count Data, Jon Wakefield
UW Biostatistics Working Paper Series
In this paper we provide critical reviews of methods suggested for the analysis of aggregate count data in the context of disease mapping and spatial regression. We introduce a new method for picking prior distributions, and propose a number of refinements of previously-used models. We also consider ecological bias, mutual standardization, and choice of both spatial model and prior specification. We analyze male lip cancer incidence data collected in Scotland over the period 1975–1980, and outline a number of problems with previous analyses of these data. A number of recommendations are provided. In disease mapping studies, hierarchical models can provide …