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April 5, 2017 | Mathematicsematical Statistics | By admin | 0 Comments

By Lance A. Waller, Carol A. Gotway

Meant for graduate scholars and researchers conversant in simple probabilistic innovations and statistical equipment, this textbook gathers spatial statistical rules built in a large number of components and discusses them within the context of often happening spatial questions in public health and wellbeing. Waller (biostatistics, Emory collage) and Gotway (Centers for sickness regulate) introduce statistical tools for the research of spatial aspect styles, expand them to choosing sickness clusters, and description tools for regression modeling utilizing spatially referenced publicity and illness information.

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Extra info for Applied Spatial Analysis of Public Health Data (Wiley Series in Probability and Statistics)

Example text

Regions have area and boundaries that may impose properties on the associated features. For example, a circle and a rectangle are both areal features, yet they are inherently different spatial objects even if they have the same area. , the NOx concentrations recorded at air monitoring stations, the racial composition of counties, the salinity of rivers). , most (nonspatial) statistical analyses examine attribute data without regard to location or support]. , we may have ozone, particulate matter, and sulfur dioxide measurements at each monitoring station; or the percentage of the population in each county self-identifying in each of several race categories).

J . Then the total number of cases expected in the study population observed (using the age-specific rates from the standard population) is J E+ = J j =1 J yj(s) j =1 n(s) j rj(s) nj = Ej = j =1 nj . The most common application of indirect standardization compares the number of cases observed in the study population, y+ , to the number of cases expected using age-specific rates from the standard population, E+ , through the standardized mortality ratio (SMR), where SMR = y+ /E+ . Some texts refer to the standardized incidence ratio (SIR) when referring to incidence rather than mortality, but the term SMR is widely used for both mortality and morbidity (including incidence), and we use SMR throughout the remainder of the text.

Fleiss (1981, pp. 239–240) reviews several valid critiques of the use of standardized rates, particularly for violations of the proportionality assumption of condition 3 above. While acknowledging that standardization does not provide a substitute for examining the age (or other stratum-specific) group’s specific rates themselves, Fleiss (1981, p. 240) offers three primary reasons for standardization: 1. , regions such as counties) rather than comparing tables of age-specific rates is relatively easy.

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