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•Multivariate data analysis of SERS maps enabled MTX prediction in patient samples.•More accurate quantification with multivariate vs. univariate data analysis.•The model can be built ...directly in commercial serum and applied to patient samples.•The genetic algorithm identified specific wavenumbers from complex SERS spectra.•Image threshold segmentation was applied to select relevant map pixels.
Despite the technological development in Raman instrumentation that has democratized access to 2D sample scanning capabilities, most quantitative surface-enhanced Raman scattering (SERS) analyses are still performed by only acquiring a single or a few spectra per sample and performing univariate data analysis on those. This strategy can however reach its limit when analytes need to be detected and quantified in complex matrices. In that case, surface fouling and competition between the target analyte and interfering compounds can impair univariate SERS data analysis, underlining the need for a more in-depth data analysis strategy based on exploiting of full-spectrum information.
In this paper, a multivariate data analysis strategy was developed, for analyzing SERS maps of methotrexate (MTX) from patient samples, including all steps from baseline correction, selection of wavelength, and the relevant pixels in the map (image threshold segmentation), as well as quantitative model construction based on partial-least squares regression.
Among the different baseline correction methods evaluated, standard normal variable transformation and Savitzky-Golay smoothing proved to be more suitable, while the genetic algorithm wavelength screening method was able to screen out MTX-related SERS spectral regions more efficiently. Importantly, with the here-developed process, it was sufficient to use MTX-spiked commercial serum when building quantitative models, removing the need to work with MTX-spiked patient samples, and consequently enabling time- and resource-saving quantitative analyses. Besides, the developed multivariate data analysis approach showed superior performances compared with univariate analysis, with 30 % improved sensitivity (detection limit of 5.7 µM), 25 % higher reproducibility (average relative standard variation of 15.6 %), and 110 % better accuracy (average prediction error of −10.5 %).
Purpose
– This article aims to draw on experience in supervising new researchers, and the advice of other writers to offer novice researchers such as those engaged in study for a thesis, or in ...another small-scale research project, a pragmatic introduction to designing and using research questionnaires.
Design/methodology/approach
– After a brief introduction, this article is organized into three main sections: designing questionnaires, distributing questionnaires, and analysing and presenting questionnaire data. Within these sections, ten questions often asked by novice researchers are posed and answered.
Findings
– This article is designed to give novice researchers advice and support to help them to design good questionnaires, to maximise their response rate, and to undertake appropriate data analysis.
Originality/value
– Other research methods texts offer advice on questionnaire design and use, but their advice is not specifically tailored to new researchers. They tend to offer options, but provide limited guidance on making crucial decisions in questionnaire design, distribution and data analysis and presentation.
This article is a review of issues associated with measuring education and using educational measures in social science research. The review is orientated towards researchers who undertake secondary ...analyses of large-scale micro-level social science datasets. The article begins with an outline of important context, which impinges upon the measurement of education. The United Kingdom is the focus of this review, but similar issues apply to other nation states. We provide a critical introduction to the main approaches to measuring education in social survey research, which include measuring years of education, using categorical qualification based measures and scaling approaches. We advocate the use of established education measures to better facilitate comparability and replication. We conclude by making the recommendation that researchers place careful thought into which educational measure they select, and that researchers should routinely engage in appropriate sensitivity analyses.
We perform a series of repeated CO
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injections in a room-scale physical model of a faulted geological cross-section. Relevant parameters for subsurface carbon storage, including multiphase flows, ...capillary CO
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trapping, dissolution and convective mixing, are studied and quantified. As part of a validation benchmark study, we address and quantify six predefined metrics for storage capacity and security in typical CO
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storage operations. Using the same geometry, we investigate the degree of reproducibility of five repeated experimental runs. Our analysis focuses on physical variations of the spatial distribution of mobile and dissolved CO
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, multiphase flow patterns, development in mass of the aqueous and gaseous phases, gravitational fingers and leakage dynamics. We observe very good reproducibility in homogenous regions with up to 97% overlap between repeated runs, and that fault-related heterogeneity tends to decrease reproducibility. Notably, we observe an oscillating CO
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leakage behavior from the spill point of an anticline and discuss the observed phenomenon within the constraints of the studied system.
This article is a review of issues associated with measuring ethnicity and using ethnicity measures in social science research. The review is oriented towards researchers who undertake secondary ...analyses of large-scale multipurpose social science datasets. The article begins with an outline of two main approaches used in social surveys to measure ethnicity, the ‘mutually exclusive category’ approach and the ‘multiple characteristics’ approach. We also describe approaches to the use of ethnicity measures in cross-national comparative research. We emphasise the value of sensitivity analyses. We also encourage researchers to carefully consider the possible relationships between ethnicity and other important variables in order to avoid spurious interpretations of the effects of ethnicity.
Why households eligible for SNAP do not participate has perplexed scholars. Explanations exist, but few explore whether SNAP nonparticipation coincides with private food assistance. Applying an ...innovative empirical strategy to SIPP data, we investigate the link between SNAP nonparticipation and private food assistance among vulnerable households with children. We find that SNAP nonparticipation is greater when households are also less likely to receive private food assistance. This finding suggests private food assistance complements SNAP participation rather than acts as a substitute. We frame this finding in terms of the welfare stigma and transactional costs literature.
Most of the academic literature on violence in Nigeria is qualitative. It rarely relies on quantitative data because police crime statistics are not reliable, or not available, or not even published. ...Moreover, the training of Nigerian social scientists often focuses on qualitative, cultural, and political issues. There is thus a need to bridge the qualitative and quantitative approaches of conflict studies. This book represents an innovation and fills a gap in this regard. It is the first to introduce a discussion on such issues in a coherent manner, relying on a database that fills the lacunae in data from the security forces. The authors underline the necessity of a trend analysis to decipher the patterns and the complexity of violence in very different fields: from oil production to cattle breeding, radical Islam to motor accidents, land conflicts to witchcraft, and so on. In addition, they argue for empirical investigation and a complementary approach using both qualitative and quantitative data. The book is therefore organized into two parts, with a focus first on statistical studies, then on fieldwork.
Mixed methods research is commonly defined as the combination and integration of qualitative and quantitative data. However, defining these two data types has proven difficult. In this article, I ...argue that qualitative and quantitative data are fundamentally different, and this difference is not about words and numbers but about condensation and structure. As qualitative data are analyzed with qualitative methods and quantitative data with quantitative methods, we cannot analyze one type of data with the other type of method. Quantitative data analysis can reveal new patterns, but these are always related to the existing variables, whereas qualitative data analysis can reveal new aspects that are hidden in the data. To consider data as quantitative or qualitative, we should judge these data as end products, not in terms of the process through which they come into being. Thus, quantitizing qualitative data results in quantitative data and the analysis thereof is quantitative, not mixed, data analysis. For mixed data analysis, both real, non-quantitized qualitative data and quantitative data are needed. As these quantitative data may be quantitized qualitative data, the implication is that, contrary to a common view, mixed methods research does not necessarily involve quantitative data collection.
This paper introduces a methodological approach building on advances in mixed-methods communication research to facilitate the integration of quantitative data into qualitative textual analysis. This ...method allows scholars working in a critical cultural media studies paradigm to incorporate quantitative data into their research to better understand media in an increasingly complicated media eco-system. This paper argues that despite calls for mixed-methods research, there are long-standing ideological and methodological tensions within the fields of Communications and Media Studies that create logistical and conceptual limitations to integrating quantitative methods in a critical cultural media studies context. This paper establishes the need for this intervention, the historical methodological contexts from which it emerges, and walks through how the approach works by looking at two possible studies using the approach in different ways.
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