21 papers · ranked by Valyu relevance
Sharada Prasad Wasti, Padam Simkhada, Edwin R. van Teijlingen, Brijesh Sathian + 1 more
This paper illustrates the growing importance of mixed-methods research to many health disciplines ranging from nursing to epidemiology. Mixed-methods approaches requires not only the skills of the individual quantitative and qualitative methods but also a skill set to bring two methods/datasets/findings together in…
Kelly A. Aschbrenner, Gina Kruse, Joseph J. Gallo, Vicki L. Plano Clark
'Vicki L. Plano Clark'] Background Pilot feasibility studies serve a uniquely important role in preparing for larger scale intervention trials by examining the feasibility and acceptability of interventions and the methods used to test them. Mixed methods (collecting, analyzing, and integrating quantitative and…
Kennedy Borle, Jehannine (J9) Austin
Mixed methods research encompasses methodological approaches that involve the collection, analysis, and integration of qualitative and quantitative data. Mixed methods are useful for complex research questions, applied research settings, and when end users value multiple forms of evidence, which makes mixed methods…
Niels Spierings, Nella Geurts
Sometimes ‘mixed methods designs’ are considered a winner for obtaining research grants, but a close-to-certain reject when publishing. Evidently, reality is more complex. At the same time, these considerations are grounded in actual experiences, observations and the structure of our epistemic community. In this…
Gudberg K. Jonsson, Mariona Portell, José Luis Losada, Judith Schoonenboom
The evolution of mixed methods research in psychological science marks a pivotal shift from the historically entrenched divide between qualitative and quantitative paradigms. Mixed methods emerged in the late twentieth century as a reconciliatory approach. By integrating diverse methodologies, it enriched psychological…
Margaret‐Anne Storey, Rashina Hoda, Alessandra Maciel Paz Milani, María Teresa Baldassarre
Engineering Authors: ['Margaret‐Anne Storey' 'Rashina Hoda' 'Alessandra Maciel Paz Milani' 'María Teresa Baldassarre'] Abstract Mixed and multi methods research is often used in software engineering, but researchers outside of the social or human sciences often lack experience when using these designs. This paper…
Elisiane Lorenzini, Sandra Patricia Osorio-Galeano, Catiele Raquel Schmidt, Wilson Cañon-Montañez
'Catiele Raquel Schmidt' 'Wilson Cañon-Montañez'] Title: Abstract Mixed methods research represents a dynamic approach, that combines quantitative and qualitative perspectives in the same study to answer complex questions, beyond the reach of each method used separately. This type of research is increasingly used in…
J. Zhu, Zibo Zhang, Jian Zhao
The study was conducted in-person or online, depending on the participant's preference, with an approximate duration of 1 hour. The study starts with a demographic survey where participants report their previous experience and confidence level in quantitative and qualitative analysis, and proficiency with analysis…
Andrew Bennett, Bear Braumoeller
This paper analyzes the working or default assumptions researchers in the formal, statistical, and case study traditions typically hold regarding the sources of unexplained variance, the meaning of outliers, parameter values, human motivation, functional forms, time, and external validity. We argue that these working…
Thomas Lynn, Julio Ottino, Richard Lueptow, Paul Umbanhowar
Cut-and-shuffle mixing is an instructive candidate system with which to assess the potential of machine learning (ML) as an approach to solve difficult mixing problems. We focus on a specific subset of cut-and-shuffle systems, the one-dimensional interval exchange transform. This class of mixing operations is well…
Yingqi Tian, Zhaoxuan Xie, Zhen Luo, Haibo Ma
Using the mixed precision strategy to optimize quantum chemistry codes has been proved promising in saving computational cost and maintaining chemical accuracy. Here, an efficient mixed-precision density matrix renormalization group (DMRG) scheme, containing a two-level mixed-precision hierarchy, is developed and…
Stephen L. France
Review and Empirical Reanalysis Authors: ['Stephen L. France'] This article gives an integrative review of research using projective methods in the consumer research domain. We give a general historical overview of the use of projective methods, both in psychology and in consumer research applications, and discuss the…
Efthymios Costa, Ioanna Papatsouma, Angelos Markos
Clustering mixed-type data, that is, observation by variable data that consist of both continuous and categorical variables poses novel challenges. Foremost among these challenges is the choice of the most appropriate clustering method for the data. This paper presents a benchmarking study comparing eight…
Georgia D Tomova, Richard J Silverwood, Peter WG Tennant, Liam Wright
This study was funded by the Survey Data Collection Methods Collaboration (known as Survey Futures), a research programme funded by the UK Economic & Social Research Council (ES/X014150/1). The UCL Centre for Longitudinal Studies is also supported by the UK Economic & Social Research Council (ES/W013142/1). The funder…
Antonino Visalli, Maria Montefinese, Giada Viviani, Livio Finos + 2 more
Mixed-effects models are the current standard for the analysis of behavioral studies in psycholinguistics and related fields, given their ability to simultaneously model crossed random effects for subjects and items. However, they are hardly applied in neuroimaging and psychophysiology, where the use of mass univariate…
Evan Gorstein, Rosa Aghdam, Claudia Solís-Lemus
High dimensional mixed-effect models are an increasingly important form of regression in modern biology, in which the number of variables often matches or exceeds the number of samples, which are collected in groups or clusters. The penalized likelihood approach to fitting these models relies on a coordinate gradient…
Authors not listed
Experimental design plays an important role in efficiently acquiring informative data for system characterization and deriving robust conclusions under resource limitations. Recent advancements in high-throughput experimentation coupled with machine learning have notably improved experimental procedures. While Bayesian…
Yangqing Deng, Dongsheng Tu, Chris J O’Callaghan, Geoffrey Liu + 1 more
In clinical research, it is of importance to study whether certain clinical factors or exposures have causal effects on clinical and patient reported outcomes like toxicities, quality of life, and self-reported symptoms, which can help improve patient care. Usually, such outcomes are recorded as multiple variables with…
Pablo Quijano Velasco, Kedar Hippalgaonkar, Balamurugan Ramalingam
The discovery of optimal conditions of chemical reactions is a labor-intensive, time-consuming task that requires exploring a high-dimensional parametric space. Historically the optimization of chemical reactions has been performed by manual experimentation guided by human intuition and Design of Experiments where one…
Ihuan Gunawan, Moumitha Dey, Daniel P Neumann, Felix V Kohane + 3 more
Multiplexed fluorescence imaging enhances spatially-resolved interrogation of complex, multi-molecular cell processes that are insufficiently sampled using standard 4-5 plex imaging. To improve accessibility and scalability for multiplexed imaging, we demonstrate generative ‘Semantic Multiplexing’ (SemaPlex); a simple…
Aniket Chitre, David Woods, Alexei Lapkin
Liquid formulations design typically involves searching a high-dimensional space, owing to the combinatorial selection of ingredients from a larger subset of available ingredients, with a relatively limited experimental budget. Therefore, we need to efficiently select the most informative experiments. These experiments…