Using an Existing Data Set to Answer New Research Questions: A Methodological Review

2009 ◽  
Vol 23 (3) ◽  
pp. 203-215 ◽  
Author(s):  
Daniel M. Doolan ◽  
Erika S. Froelicher
Keyword(s):  
Data Analysis ◽  
Research Question ◽  
Secondary Analysis ◽  
Secondary Data ◽  
Secondary Data Analysis ◽  
Data Set ◽  
Research Questions ◽  
Conducting Research ◽  
New Research ◽  
Existing Data

The vast majority of the research methods literature assumes that the researcher designs the study subsequent to determining research questions. This assumption is not met for the many researchers involved in secondary data analysis. Researchers doing secondary data analysis need not only understand research concepts related to designing a new study, but additionally must be aware of challenges specific to conducting research using an existing data set. Techniques are discussed to determine if secondary data analysis is appropriate. Suggestions are offered on how to best identify, obtain, and evaluate a data set; refine research questions; manage data; calculate power; and report results. Examples from nursing research are provided. If an existing data set is suitable for answering a new research question, then a secondary analysis is preferable since it can be completed in less time, for less money, and with far lower risks to subjects. The researcher must carefully consider if the existing data set’s available power and data quality are adequate to answer the proposed research questions.

scholarly journals Exploring youth information-seeking behaviour and mobile technologies through a secondary analysis of qualitative data

2018 ◽  
Vol 50 (3) ◽  
pp. 322-331 ◽  
Author(s):  
Leanne Bowler ◽  
Heidi Julien ◽  
Leslie Haddon
Keyword(s):  
Data Analysis ◽  
Information Seeking ◽  
Qualitative Data ◽  
Secondary Analysis ◽  
Secondary Data ◽  
Secondary Data Analysis ◽  
Mobile Technologies ◽  
The European Union ◽  
Data Set ◽  
Information Behaviour

This paper examines issues associated with secondary analysis of qualitative data and their implications for information behaviour scholarship. Secondary data analysis poses a range of potential challenges for data creators, but also opportunities, including the ability to expand theory to a wider context, strengthen the reliability and validity of existing theory, gain access to populations that may be difficult to access, and to promote data archiving. The paper uses as a case study of secondary data analysis the results from our re-examination of data gathered previously in the European Union project Net Children Go Mobile, drawing from the interview transcripts from the 34 children in the UK data set. Our approach to secondary analysis was reanalysis, applying a new interpretive lens to the data that necessitated new questions in order to reveal hidden layers in the data. The data was analysed for evidence of information behaviour in order to understand how mobile technologies may be changing the way that young people seek and use information. The reanalysis of the data set supported existing models of information behaviour but revealed new ways of information seeking based on the affordances of screen size and data plans.

scholarly journals Secondary Data Analysis: Lessons and perspective of a research parasite

2021 ◽  
Author(s):  
Ayush Raman
Keyword(s):  
Data Analysis ◽  
Signal To Noise Ratio ◽  
Secondary Analysis ◽  
Scientific Progress ◽  
Secondary Data ◽  
Secondary Data Analysis ◽  
Research Directions ◽  
Award Recipient ◽  
Junior Research ◽  
New Research

Secondary data analysis refers to re-analyzing publicly available datasets to investigate the questions that original scientists had not posited. This helps in scientific progress by paving the path to more reliable and robust analyses and new research directions without any considerable expense. However, these datasets are anything but perfect, and researchers must investigate and assess the signal to noise ratio robustly to extract meaningful information. These efforts of rigorous secondary analysis are further recognized and supported by the Research Parasite Awards. As the 2020 Junior Research Parasite Award recipient, I share my journey and perspective of a research parasite in this commentary article.

scholarly journals Recommendations for increasing the transparency of analysis of pre-existing datasets

2018 ◽  
Author(s):  
Sara J Weston ◽  
Stuart James Ritchie ◽  
Julia Marie Rohrer ◽  
Andrew K Przybylski
Keyword(s):  
Data Analysis ◽  
Secondary Data ◽  
Open Science ◽  
Secondary Data Analysis ◽  
Science Practices ◽  
Advantages And Disadvantages ◽  
Analytic Methods ◽  
Technological Advances ◽  
Methodological Tool ◽  
Existing Data

Secondary data analysis, or the analysis of pre-existing data, can be a powerful tool for the resourceful researcher. Never has this been more true than now, when technological advances allow for easier sharing of data across labs and continents and the mining of large sources of “pre-existing data”. However, secondary data analysis is often ignored as a methodological tool, either when developing new open science practices or improving analytic methods for robust data analysis. In this paper, we hope to provide researchers with the knowledge necessary to incorporate secondary data analysis into their toolbox. Specifically, we define secondary data analysis as a tool and in relation to other common forms of analysis (including exploratory and confirmatory, observational and experimental). We highlight the advantages and disadvantages of this tool. We describe how engagement in transparency can improve and alter our interpretations of results from secondary data analysis and provide resources for robust data analysis. We close by suggesting ways in which subfields and institutions could address and improve the use of secondary data analysis.

scholarly journals Conducting secondary analysis of qualitative data: Should we, can we, and how?

2017 ◽  
Vol 18 (1) ◽  
pp. 81-97 ◽  
Author(s):  
Nicole Ruggiano ◽  
Tam E Perry
Keyword(s):  
Data Analysis ◽  
Best Practices ◽  
Qualitative Data ◽  
Secondary Analysis ◽  
Secondary Data ◽  
Secondary Data Analysis ◽  
Ethical Problems ◽  
Current State ◽  
Critical Interpretive Synthesis ◽  
Recommended Guidelines

While secondary data analysis of quantitative data has become commonplace and encouraged across disciplines, the practice of secondary data analysis with qualitative data has met more criticism and concerns regarding potential methodological and ethical problems. Though commentary about qualitative secondary data analysis has increased, little is known about the current state of qualitative secondary data analysis or how researchers are conducting secondary data analysis with qualitative data. This critical interpretive synthesis examined research articles (n = 71) published between 2006 and 2016 that involved qualitative secondary data analysis and assessed the context, purpose, and methodologies that were reported. Implications of findings are discussed, with particular focus on recommended guidelines and best practices of conducting qualitative secondary data analysis.

scholarly journals The Relationship between Administrative Intensity and Student Retention and Success: A Three-Year Study

2018 ◽  
Vol 8 (4) ◽  
pp. 159 ◽  
Author(s):  
Kerry Romine ◽  
Rose Baker ◽  
Karla Romine
Keyword(s):  
Higher Education ◽  
Data Analysis ◽  
Student Retention ◽  
Postsecondary Education ◽  
Graduation Rates ◽  
Secondary Data ◽  
Secondary Data Analysis ◽  
Policy Implications ◽  
Education Student ◽  
Data Set

Through the lens of complexity theory and by utilizing the methodological framework set forth in Gander’s 1999 article regarding internal and external organizational elements of administrative intensity, this secondary data analysis study linked the internal organizational elements of administrative intensity to institutional results as evidenced by higher education student retention and graduation rates. Representing institutional investments, efforts, and outcomes from 2004 to 2014, three years of data reporting were gathered from the Integrated Postsecondary Education Data Set (IPEDS) and were then cleaned per secondary data analysis techniques. Using canonical correlation analysis, the internal elements of administrative intensity were correlated with student retention and success. Findings indicate the relationships of internal elements of higher education institutions on student retention and success, which was measured by four-year, six-year, and eight-year graduation rates. The discussion includes education policy implications.

scholarly journals West-African Modes of Mobilisations Confronting EU Mobility Regimes

2020 ◽  
Vol 47 (2) ◽  
Author(s):  
Julia Söhnholz
Keyword(s):  
Social Movements ◽  
Data Analysis ◽  
Research Question ◽  
Secondary Data ◽  
Secondary Data Analysis ◽  
West African ◽  
Political Agency ◽  
Future Research ◽  
Transnational Social Movements ◽  
Inherent Part

Abstract: This article explores West-African modes of mobilisations confronting the externalisation of European borders. At the hands of a secondary data analysis, this article critically examined the most recent publications in relation to this topic, guided by the following research question: How do West-African modes of mobilisations challenge EU mobility regimes? This research identified governments, local organisations, (potential) migrants, expelled migrants, media, academia and writers and transnational social movements as relevant actors with different modes of action. This research suggests that there are multiple West-African modes of mobilisations that challenge EU mobility regimes, confront the problematisation of non-sedentary lifestyles and see mobility as a strategy and a solution for a bottom-up process of globalisation and as an inherent part of West-African mobile societies; existing next to African modes of mobilisations that have become part of EU mobility regimes. The objective of this research is to promote future research by increasing the visibility and political agency of the transformative possibilities of African modes of mobilisations.

scholarly journals Protecting against researcher bias in secondary data analysis: challenges and potential solutions

2022 ◽  
Author(s):  
Jessie R. Baldwin ◽  
Jean-Baptiste Pingault ◽  
Tabea Schoeler ◽  
Hannah M. Sallis ◽  
Marcus R. Munafò
Keyword(s):  
Data Analysis ◽  
Secondary Data ◽  
Evidence Base ◽  
Secondary Data Analysis ◽  
Questionable Research Practices ◽  
Administrative Records ◽  
Alternative Approaches ◽  
Secondary Data Sources ◽  
Existing Data ◽  
Researcher Bias

AbstractAnalysis of secondary data sources (such as cohort studies, survey data, and administrative records) has the potential to provide answers to science and society’s most pressing questions. However, researcher biases can lead to questionable research practices in secondary data analysis, which can distort the evidence base. While pre-registration can help to protect against researcher biases, it presents challenges for secondary data analysis. In this article, we describe these challenges and propose novel solutions and alternative approaches. Proposed solutions include approaches to (1) address bias linked to prior knowledge of the data, (2) enable pre-registration of non-hypothesis-driven research, (3) help ensure that pre-registered analyses will be appropriate for the data, and (4) address difficulties arising from reduced analytic flexibility in pre-registration. For each solution, we provide guidance on implementation for researchers and data guardians. The adoption of these practices can help to protect against researcher bias in secondary data analysis, to improve the robustness of research based on existing data.

scholarly journals Variance & Homogeneity of Facial Trait Space Across World Regions [PSA001 Secondary Data Analysis]

2020 ◽  
Author(s):  
Sally Y Xie ◽  
Eric Hehman
Keyword(s):  
Data Analysis ◽  
Secondary Analysis ◽  
Secondary Data ◽  
Secondary Data Analysis ◽  
Psychological Science ◽  
World Regions ◽  
Trait Impressions ◽  
Trait Space

This preregistration is part of the PSA secondary analysis challenge. We investigate how the facial 'trait space' shifts across countries and world regions, using the PSA_001 dataset shared by the Psychological Science Accelerator. The facial trait space refers to the interrelationships between many of the trait impressions that people infer from faces. Here, we examine whether this trait space is more homogeneous (or less differentiated) in some cultures than others.

Barriers for homeless with dual diagnosis: lessons learned from intensive mobile psychosocial assertive community treatment program

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tara Rava Zolnikov ◽  
Michael Hammel ◽  
Frances Furio ◽  
Brandon Eggleston
Keyword(s):  
Data Analysis ◽  
Effective Treatment ◽  
Dual Diagnosis ◽  
Treatment Program ◽  
Assertive Community Treatment ◽  
Secondary Analysis ◽  
Secondary Data ◽  
Secondary Data Analysis ◽  
Community Treatment ◽  
Content Type

Purpose Dual diagnosis is a term that describes the co-occurrence of mental health disorders or illness and substance use or abuse disorders. Because this co-occurrence results in multiple diseases, layers of treatment are often needed to successfully create positive change in the individual. The purpose of this study is to explore factors of treatment that could facilitate improvements in functionality and quality of life for those with a dual diagnosis. Design/methodology/approach A secondary data analysis, using both quantitative and qualitative data, was completed. Secondary analysis is an empirical exercise that applies the same basic research principles as studies using primary data and has steps to be followed, including the evaluative and procedural steps commonly associated with secondary data analysis. Documentation data from the intensive mobile psychosocial assertive community treatment program was gathered for this analysis; this program was used because of the intensive and community-based services provided to patients with a dual diagnosis. Findings The major findings from this secondary analysis suggested that significant barriers included “denial” (e.g. evasion, suspension or avoidance of internal awareness) of diagnoses, complicated treatment and other barriers related to housing. Ultimately, these findings provided greater insight into potential effective treatment interventions for people living with a dual diagnosis. Originality/value This study adds to the growing body of literature showing that patient-centered care allows for more effective treatment and ultimately, improved health outcomes.

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