Archival storage of data sets from qualitative studies presents opportunities for combining small-scale data sets for reuse/secondary analysis. In this paper, we outline our approach to combining multiple qualitative data sets and explain why working with a corpus of 'big qual' data is a worthwhile endeavour. We present a new approach that iteratively combines recursive surface thematic mapping and in-depth interpretive work. Our breadth-and-depth method involves a series of steps: (1) surveying archived data sets to create a new assemblage of data; (2) recursive surface thematic mapping in dialogue with (3) preliminary 'test pit' analysis, remapping and repetition of preliminary analysis; and (4) in-depth analysis of the type that is familiar to most qualitative researchers. In so doing, we show how qualitative researchers can conduct 'big qual' analysis while retaining the distinctive order of knowledge about social processes that is the hallmark of rigorous qualitative research, with its integrity of attention to nuanced context and detail.
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http://dx.doi.org/10.1007/s11135-018-0757-y | DOI Listing |
Lifetime Data Anal
January 2025
Institut Camille Jordan, UMR 5208, Université Claude Bernard Lyon 1, Bat. Braconnier, 43, blvd du 11 novembre 1918, F - 69622, Villeurbanne Cedex, France.
Based on the expectile loss function and the adaptive LASSO penalty, the paper proposes and studies the estimation methods for the accelerated failure time (AFT) model. In this approach, we need to estimate the survival function of the censoring variable by the Kaplan-Meier estimator. The AFT model parameters are first estimated by the expectile method and afterwards, when the number of explanatory variables can be large, by the adaptive LASSO expectile method which directly carries out the automatic selection of variables.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Department of Urology, Ji'an Third People's Hospital, Ji'an 343000, Jiangxi, China.
As combination therapy becomes more common in clinical applications, predicting adverse effects of combination medications is a challenging task. However, there are three limitations of the existing prediction models. First, they rely on a single view of the drug and cannot fully utilize multiview information, resulting in limited performance when capturing complex structures.
View Article and Find Full Text PDFMol Ecol Resour
January 2025
Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
Reduced representation sequencing (RRS) has proven to be a cost-effective solution for sequencing subsets of the genome in non-model species for large-scale studies. However, the targeted nature of RRS approaches commonly introduces large amounts of missing data, leading to reduced statistical power and biased estimates in downstream analyses. Genotype imputation, the statistical inference of missing sites across the genome, is a powerful alternative to overcome the caveats associated with missing sites.
View Article and Find Full Text PDFMayo Clin Proc Digit Health
December 2024
School of Computed and Augmented Intelligence, Arizona State University, Tempe, AZ.
Objective: To report the development and performance of 2 distinct deep learning models trained exclusively on retinal color fundus photographs to classify Alzheimer disease (AD).
Patients And Methods: Two independent datasets (UK Biobank and our tertiary academic institution) of good-quality retinal photographs derived from patients with AD and controls were used to build 2 deep learning models, between April 1, 2021, and January 30, 2024. ADVAS is a U-Net-based architecture that uses retinal vessel segmentation.
J Adv Nurs
January 2025
Department of Nursing and Midwifery, College of Health Wellbeing & Life Sciences, Sheffield Hallam University, Sheffield, UK.
Aim: To highlight the use of corpus linguistics for analysing language data and to provide a worked example of this approach in nursing research.
Design: Methodology discussion paper.
Methods: This paper introduces corpus linguistics as a distinct approach to undertaking qualitative research in nursing.
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