Uncertainty In Quantitative Analysis Research Articles

Methodological Uncertainty and Multi-Strategy Analysis: Case Study of the Long-Term Effects of Government Sponsored Youth Training on Occupational Mobility

Sociological practitioners often face considerable methodological uncertainty when undertaking a quantitative analysis. This methodological uncertainty encompasses both data construction (e.g. defining variables) and analysis (e.g. selecting and specifying a modelling procedure). Methodological uncertainty can lead to results that are fragile and arbitrary. Yet, many practitioners may be unaware of the potential scale of methodological uncertainty in quantitative analysis, and the recent emergence of techniques for addressing it. Recent proposals for ‘multi-strategy’ approaches seek to identify and manage methodological uncertainty in quantitative analysis. We present a case-study of a multi-strategy analysis, applied to the problem of estimating the long-term impact of 1980s UK government-sponsored youth training. We use this case study to further highlight the problem of cumulative methodological fragilities in applied quantitative sociology and to discuss and help develop multi-strategy analysis as a tool to address them.

Oxygen determination in materials by 18O(p,αγ)15N nuclear reaction

The paper presents a proton induced γ-ray emission method based on 18O(p,αγ)15N nuclear reaction to determine bulk oxygen in materials. The determination involves the measurement of 5.27MeV γ-rays emitted following the de-excitation of 15N nuclei. A description of the energetics of the reaction is given to provide an insight into the origin of 5.27MeV γ-rays. In addition, thick target γ-ray yields and the limits of detection are measured to ascertain the analytical potential of the reaction. The thick-target γ-ray yields are measured with a high purity germanium detector and a bismuth germanate detector at 0° as well as 90° angles in 3.0–4.2MeV proton energy region. The best limit of detection of about 1.3at.% is achieved at 4.2MeV proton energy for measurements at 0° as well 90° angles with the bismuth germanate detector while the uncertainty in quantitative analysis is <8%. The reaction has a probing depth of several tens of microns. Interferences can arise from fluorine due to the occurrence of 19F(p,αγ)16O reaction that emits 6–7MeV γ-rays. The analytical potential of the methodology is demonstrated by determining oxygen in several oxide as well as non-oxide materials.

GC-NCI-MS/MS를 이용한 모발 중 대마 대사체 분석의 측정불확도 평가

대마 흡연 여부 확인을 위해 사용되는 모발 중 대마 대사체 정량분석 결과의 측정불확도를 평가하였다. 대마초 성분 중 활성물질은 <TEX>${\Delta}^9$</TEX>-tetrahydrocannabinol이며 대사과정을 거쳐 생성된 주요 대사체는 11-nor-9-carboxy-<TEX>${\Delta}^9$</TEX>-tetrahydrocannabinol (THC-COOH)이다. 따라서 생체 대사물질인 THC-COOH는 대마 흡연 여부를 판단하는 지표물질로 사용되고 있다. 실험방법은 모발의 세척, 건조, 질량측정, 세절, 가수분해, 비드를 이용한 액체-액체 추출, 유도체화 반응 및 기기분석 과정으로 구성되었다. 측정의 소급성이 유지될 수 있도록 상위 규정기로부터 하위 측정기까지 교정을 통해 확보하였다. 측정불확도 평가에 앞서 정량분석시 측정값에 영향을 주는 인자들을 찾아내고 각각의 요소들이 측정결과에 어떤 영향을 주는가를 살펴보았다. 산출 결과, 재현성, 회수율, 검정곡선, 표준물질, 질량측정의 요소 순으로 불확도에 영향을 미치고 있음을 확인하였고 재현성의 요소가 측정불확도에 가장 큰 영향을 미치고 있었다. 실제 대마 복용자의 모발을 분석한 결과 대마 대사체 농도 측정값에 대한 오차 범위의 상대불확도는 17% 이였으며, 본 연구의 측정불확도 평가 결과는 향후 분석방법의 개선 및 측정결과의 신뢰도 제고를 위한 근거자료로 활용할 예정이다. We described an estimation of measurement uncertainty in quantitative analysis of 11-nor-9-carboxy-<TEX>${\Delta}^9$</TEX>-tetrahydrocannabinol (THC-COOH), the metabolite of <TEX>${\Delta}^9$</TEX>-tetrahydrocannabinol, in hair samples by using the bead-assisted liquid-liquid extraction and gas chromatography-tandem mass spectrometric (GC-NCI-MS/MS) detection. Traceability of measurement was established through the use of reference materials, calibrated volumetric tubes, volume measuring devices, and measuring instruments. The analytical results were compared and the different contributions to the uncertainty were evaluated. Inter-day variation was performed by using statistical analysis of several indicative factors. Measurement uncertainty associated with the analyte in real forensic hair samples were estimated using QC data. The major factor of contribution to combined standard uncertainty was inter-day repeatability, while those associated with preparation of analytical standard and also sample of weight were insignificant considering the degree of contribution. Relative uncertainty of relative extended standard uncertainty divided into the measured concentration of the analyte was 17% in a hair sample. The uncertainty of result evaluation will be invaluable to improve quality of the analysis.

Calculation of Measurement Uncertainty in Quantitative Analysis of Genetically Modified Organisms Using Intermediate PrecisionA Practical Approach

Quantitative characterization of nucleic acids is becoming a frequently used method in routine analysis of biological samples, one use being the detection of genetically modified organisms (GMOs). Measurement uncertainty is an important factor to be considered in these analyses, especially where precise thresholds are set in regulations. Intermediate precision, defined as a measure between repeatability and reproducibility, is a parameter describing the real situation in laboratories dealing with quantitative aspects of molecular biology methods. In this paper, we describe the top-down approach to calculating measurement uncertainty, using intermediate precision, in routine GMO testing of food and feed samples. We illustrate its practicability in defining compliance of results with regulations. The method described is also applicable to other molecular methods for a variety of laboratory diagnostics where quantitative characterization of nucleic acids is needed.

Including uncertainty in assessments of sulfur oxide health risks.

Methods for the incorporation of uncertainty in quantitative analysis are needed in risk assessment applications, such as the problem of estimating health risks from coal-fired power plants. Techniques including elicitation of subjective expert judgment about uncertainty and stochastic simulation modeling are combined in a demonstration analysis. Probabilistic estimates of population exposure to sulfur air pollution from a hypothetical new power plant are generated for two locations in the Ohio River Valley. Models of health responses to air pollution, obtained through elicitation of the judgment of seven leading health scientists, are applied to these exposure estimates, and uncertainty about the level of health impacts is predicted and compared. The predictions range from a significant probability of zero health effects to a small probability of effects on the order of 20 percent of the total mortality. Uncertainty about the adverse effects of sulfur air pollution on human health is far greater than the scientific uncertainty about the atmospheric processes which generate and transport it. These techniques have the potential to improve our understanding and ability to communicate about scientific uncertainty about risk, and may be useful for the analysis of the benefits of sulfur air pollution control.

Quantitative analysis of first and second surface layers by LEIS (TOF)

The time-of-flight version of low energy ion scattering LEIS (TOF), avoids uncertainties in quantitative analysis due to neutralization in scattering. However, some other factors to consider are: a) accuracy of the scattering cross-sections employed, b) enhancement of scattering yields from sub-surface layers by focusing effects, c) dependence of detector efficiency on scattered energy, and d) background subtraction in integration of single-scattering peaks. We have investigated these problems using 2.4–10 keV Ne + beams scattered from a Cu 3Au (100) ordered surface in conjunction with computer simulation of the energy spectra and have found c) to be the most important potential source of error. Correction factors are derived from measurements of scattering yield vs E 0.