Representativeness. A public health surveillance system that is representative accurately describes the occurrence of a health-related event over time and its distribution in the population by place and person (Updated Guidelines for Evaluating Public Health Surveillance Systems: Recommendations from the Guidelines Working Group, MMWR, 2001). A comprehensive literature review of GHBS related documentation and information collected from key informant interviews provided information about the representativeness of the IDU population. For many health-related events under surveillance, the proper analysis and interpretation of the data require the calculation of rates (Updated Guidelines for Evaluating Public Health Surveillance Systems: Recommendations from the Guidelines Working Group, MMWR, 2001). The denominators for these rate calculations are often obtained from a completely separate data system maintained by another agency (Updated Guidelines for Evaluating Public Health Surveillance Systems: Recommendations from the Guidelines Working Group, MMWR, 2001). GHBS informed the evaluator that GHBS staff has reached its enrollment goal of 500 participants for IDU cycle II and IDU cycle III. There is somewhat of an issue with representativeness of the sample because the majority of the population is surveyed in areas in Xxxxxx County. However, the CDC and GHBS staff would like to find strategic ways to reach individuals who inject drugs in other counties. However, the staff is limited to conducting research in Xxxxxx County due to costs associated with having multiple storefronts in multiple counties. The GHBS system is representative of the type of population for which they are trying to reach, which is IDUs. However, there is a challenge with trying to get a more representative sample of women and different ethnicities who inject drugs. Additionally, funding restrictions places limitations on reaching other IDUs who live in the areas outside of Xxxxxx County.
Representativeness. Representativeness is a qualitative measure of the degree to which data accurately and precisely reflects a characteristic of a population or measurement location. Representativeness will be achieved through careful, informed selection of sampling sites, drilling depths, and analytical parameters and through the proper collection and handling of samples to avoid interference and minimize sample cross-contamination and loss. The evaluator makes a determination, based on professional judgment, as to whether the data obtained during the survey can be considered representative of a particular survey unit.
Representativeness. The data logger stations have been placed in such locations in each sub-watershed as logistical constraints have permitted and where the purpose of the monitoring program can be accomplished (Figure 3 and Figure 4). The majority of the stations have been monitored under CKCD’s ambient monitoring program since 1995. Each station was initially chosen to be representative of typical stream conditions and surrounding land use practices. Site accessibility was also taken into consideration during the site selection process. CKCD feels that it is important for our study to utilize pre-existing monitoring sites, so that data collected during the course of this grant can be compared directly to historical data collected at the same locations. To assess representativeness, the CKCD District Manager will review field monitoring documentation to determine if external circumstances may have affected the field measurements. Water quality samples will be collected from stream locations that measure a representative sample of the stream. Samples should be collected from the main flow, but not in a backwater or eddy. When possible, grab samples should be collected far enough below the water surface to avoid sampling surface water. Temperature data loggers should not be placed too near the substrate in a groundwater upwelling reach, but deep enough to remain in the water at low flow. Water quality samples are intended to be representative of stream conditions at the locations and time of collection. Monthly samples may estimate seasonal changes. Continuous temperature loggers will record every 30 minutes to estimate diurnal and seasonal temperature changes.
Representativeness. The limiting factor to representativeness is the availability of a large sample population. Experimental designs will be constructed such that projects will either have sufficiently large sample populations per trial or statistically significant fractional populations. The tests will be conducted at the paint and equipment supplier-recommended operating conditions. If the test data obtained from standard materials meet the quantitative QA criteria (precision, accuracy, and completeness), the measurements of the tested samples will be considered representative of the coating technologies under evaluation and used to interpret the outcomes relative to the specific project objectives.
Representativeness. Data representativeness is defined as the degree to which data accurately and precisely represents a characteristic of a population, parameter, and variations at a sampling point, a process condition, or an environmental condition. It therefore addresses the natural variability or the spatial and temporal heterogeneity of a population. The number of sampling points and their location within the study area will be examined to ensure that representative sample collection of each area of the watersheds and each target analyte series occurs. Multiple sampling episodes will be conducted over a period of 6 months to obtain sufficient data to determine analyte concentration variability.
Representativeness. The representativeness of the data is mainly dependent on the sampling locations and the sampling procedures adequately representing the true condition of the sample site. Requirements for selecting sample sites are discussed in more detail in the protocol narrative. Selection of appropriate sample sites and the use of only approved/documented analytical methods will ensure that the measurement data does represent the conditions at the investigation site, to the extent possible. Assuring representativeness of the data will be accomplished by using methods used by the USGS (collector sites, cross-section checks, sampling from the centroid of flow, etc.) A combination of assuring representativeness, plus selecting sites upstream of bridges and culverts (as detailed in Standard Operating Procedure (SOP #12, Site Selection & Documentation)), and randomly selecting where to start sampling the midpoints and cross-sections upstream will assure both reasonable representativeness of the target population while still maintaining good data comparability with regional USGS data Some constraints to sampling representatively include difficult or unsafe access, particularly during storm events. Also, due to laboratory closures and lack of staff availability during the winter holidays when major storm events often occur, valuable water quality data may not be captured. Other constraints to sampling representatively are that sites will primarily be located within park boundaries and will not necessarily represent the larger watershed. This will not be a significant concern since parks encompass several watersheds in their entirety. However, watersheds with significant portions located outside park boundaries may not be sampled in some cases due to access issues, relative lack of management options, or other limitations.
