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1 etermine body burdens based on individual or population characteristics.
2 ow that this model produces many of the same population characteristics.
3 ity at population level, after adjusting for population characteristics.
4 ut any specific hypothesis-testing or unique population characteristics.
5 relationship between patch test results and population characteristics.
6 come, and establish recovery trajectories by population characteristics.
7 surface and analyzed their distribution and population characteristics.
8 ion, and marital status, as well as zip code population characteristics.
9 ient population and relates this severity to population characteristics.
10 vironment such as maternal family, group and population characteristics affected the age at which mal
11 comes, but this relationship could depend on population characteristics and adiposity indicator emplo
14 ion in factors such as sampling methodology, population characteristics and marker system can all lea
17 t starting ages and intervals will depend on population characteristics and the decision makers' weig
19 r than 60 years with STEMI, changes in other population characteristics, and greater use of reperfusi
20 inical diagnosis, exposure assessment, study population characteristics, and identification of data g
21 extract data on study design, interventions, population characteristics, and outcomes; evaluate study
27 explained in part by differences in patient population characteristics, CT technique, and interobser
29 main predictors of mortality variations were population characteristics, especially age and socio-eco
31 ociations between these disease patterns and population characteristics have not been determined.
33 CHD mortality are predominantly explained by population characteristics; however, greater detection o
34 ortality rate as the dependent variable, and population characteristics (index of multiple deprivatio
37 dently abstracted trial-level data including population characteristics, interventions, clinical outc
38 e abstracted information about study design, population characteristics, interventions, outcomes, and
41 is study was to assess the impact of patient population characteristics on accuracy by computed tomog
42 viewed the literature on the extent to which population characteristics or clinical features predict
43 by geographic variation, difference in host population characteristics, or differences in sampling m
46 ficient and accepted means of assessing many population characteristics, risk factors, and diseases,
47 women meeting (in addition to the underlying population characteristics) strict individual eligibilit
48 study, and authors and we extracted data for population characteristics such as the number of pregnan
49 or phantom models using the specific patient population characteristics such as total body and inject
50 y often result in more accurate estimates of population characteristics that are of interest in epide
51 ificantly to resistance to infection, B(Mem) population characteristics that may relate to protective
52 severe infections or super-shedding events - population characteristics that should be further invest
53 nd comparators, study setting, study design, population characteristics, the proportion of infants co
55 suggest that more attention must be paid to population characteristics to identify greater likelihoo
56 the same institution to determine if patient population characteristics, treatment approaches, and cl
62 isted after statistical adjustment for those population characteristics, which differed slightly betw
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