Surveys data quality evaluation

Applications of geological reference samples to mineral prospecting and economic evaluation of ore potential is the only application with a history dating back before the issuance of G-i and W-i in 1951. It is an area in which data quality or lack thereof has serious economic impacts, hence the very early development of certified reference materials mentioned previously. An extensive study of the state of ore analysis was undertaken by the Institute of Geological Sciences (now the British Geological Survey). Nineteen ores and concentrates, of varied matrix, were distributed to 38 laboratories more than 1532 results were received (Lister and Galagher 1970). 

L. Jorhem, J. Engman, B. Sundstrom, A. Nilsson, Evaluation of measurement data for Cd, Cr and Pb in certain uncontaminated foodstuffs published in surveys analytical quality vs. uncertainty of measurements, J. Accred. Qual. Assur., 10 (2006), 647-658. 

Both interview and questionnaire techniques were used in this survey. Fifty, semi-structured interviews were conducted on-site with a randomly selected, representative, stratified sample of employees. (See Appendix B for an example of some of the prompt questions used in the interview note that this can only be developed after some open interviews/discussion sessions are completed.) A questiormaire was generated from the interview data and distributed to 520 staff to be completed anonymously. This produced a 45 per cent usable response rate for analysis. The objectives were to gain an understanding of the perceptions of quality within the company and readiness for change to provide baseline data for evaluation purposes to identify quality improvement opportunities and potential barriers to change and to help management develop a sense of awareness about quality and quality improvement needs in the plant. The questionnaire included measures of job satisfaction (Warr et aL, 1979), organizational commitment (Porter et al., 1974), perceptions of cooperation and morale in the plant and measures of certain job characteristics associated with quality work performance, such as skill variety, autonomy and feedback (Hackman and Oldham, 1975). 

The extent of the survey is based on regional studies, with the requirements for data quality and quantity set forth in Refe [1,6]. The investigation is site-specific and covers an area within an approximately 50 km radius of the site. This area may be extended to compensate for lack of data in the time record (see Section 6.2). It may be smaller if the area is not populated and possible causes of events do not exist. The record length to be considered for site-specific evaluation is chosen with reference to the return period selected for the design basis. Appropriate extrapolation techniques have to be applied and validated. The projected growth of population around the site during the lifetime of the facility is evaluated. 

Ocean Data Evaluation System (ODES) Data Submissions Manual QA/QC Guidance for Sampling and Analysis of Sediments Water and Tissue for Dredged Material Evaluations Chemical Evaluations Quality Assurance Plan for the National Pesticide Survey of Drinking Water Wells Analytical Method 2, Chlorinated Pesticides Quality Assurance Project Plan for Analytical Control and Assessment Activities in the National Study of Chemical Residues in Lake Fish Tissue... 

Danish mathematician George Rasch developed the Rasch model (5). Researchers can use the Rasch model to develop tests and surveys, monitor the quality of survey or test data, improve test or survey items, and calculate an equal interval total score for both test takers and survey respondents. When researchers evaluate data using parametric statistical tests (e.g., t-test, ANOVA), they assume that score data is " equal interval. We can use the Rasch analysis software to convert non-equal interval data into equal interval data. In recent years, evaluators have used the Rasch model for large-scale, assessment projects such as the evaluation of reform in the Chicago Public Schools (6)... 

It is impossible to present more than gross estimates of world resources of fertilizer raw materials for several reasons. Although man continues to explore his environment and many areas of the globe have been ex--plored in detail, particularly in the last 30 years, there are areas of the globe that have not been surveyed or have been surveyed inadequately. When deposits are known to exist, the extent and quality of information on the quantity or quality of material in the deposit may vary greatly. Reasonably good data may only exist when considerable effort and funds have been spent to develop deposits. Detailed exploration and evaluation of a deposit is an expensive process only undertaken when commercial exploitation is probable. 

Once the key questions have been articulated, it is important to consider the source of the information and how the data may be collected within resource constraints of the program. Effective program evaluation makes use of multiple data collection methods at multiple points in the program. Some of the methods used in existing programs to determine quality and design plans for continuous improvement are described here. These include document reviews, interviews, surveys, instructor reflections, expert reviews, and longitudinal studies. 

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