Abstract：
:Cross-national research on health system performance can yield important findings for public policy purposes. We seek to further this research by examining the problem of selection bias, an important methodological issue that investigators initially should consider. Because of the logistical difficulties and enormous expense involved in collecting voluminous data from many countries, researchers often must rely on information contained in data sets of international organizations, such as the World Health Organization (WHO) and the Organization for Economic Cooperation and Development. Under the circumstances, the comparisons that researchers can make will depend to a great extent on the availability and richness of data for certain measures. This situation raises the potential for selection or experimenter bias. We use multivariate statistics to group countries with similar characteristics, an approach that we believe will mitigate the problem. We perform a cluster analysis of 186 countries using principal components derived from 7 demographic variables and 27 mortality and burden of disease variables. Our analysis produced six clusters that we believe represent suitable groupings for comparative purposes.
journal_name
Health Placejournal_title
Health & placeauthors
Bauer DT,Ameringer CFdoi
10.1016/j.healthplace.2010.07.004subject
Has Abstractpub_date
2010-11-01 00:00:00pages
1129-35issue
6eissn
1353-8292issn
1873-2054pii
S1353-8292(10)00095-Xjournal_volume
16pub_type
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