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Declaring and Diagnosing Research Designs

Researchers need to select high-quality research designs and communicate those designs clearly to readers. Both tasks are difficult. We provide a framework for formally “declaring” the analytically relevant features of a research design in a demonstrably complete manner, with applications to qualita...

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Detalles Bibliográficos
Autores principales: BLAIR, GRAEME, COOPER, JASPER, COPPOCK, ALEXANDER, HUMPHREYS, MACARTAN
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7449569/
https://www.ncbi.nlm.nih.gov/pubmed/32855557
http://dx.doi.org/10.1017/s0003055419000194
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author BLAIR, GRAEME
COOPER, JASPER
COPPOCK, ALEXANDER
HUMPHREYS, MACARTAN
author_facet BLAIR, GRAEME
COOPER, JASPER
COPPOCK, ALEXANDER
HUMPHREYS, MACARTAN
author_sort BLAIR, GRAEME
collection PubMed
description Researchers need to select high-quality research designs and communicate those designs clearly to readers. Both tasks are difficult. We provide a framework for formally “declaring” the analytically relevant features of a research design in a demonstrably complete manner, with applications to qualitative, quantitative, and mixed methods research. The approach to design declaration we describe requires defining a model of the world (M), an inquiry (I), adatastrategy(D), andananswerstrategy(A). Declaration of these features in code provides sufficient information for researchers and readers to use Monte Carlo techniques to diagnose properties such as power, bias, accuracy of qualitative causal inferences, and other “diagnosands.” Ex ante declarations can be used to improve designs and facilitate preregistration, analysis, and reconciliation of intended and actual analyses. Ex post declarations are useful for describing, sharing, reanalyzing, and critiquing existing designs. We provide open-source software, DeclareDesign, to implement the proposed approach.
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spelling pubmed-74495692020-08-26 Declaring and Diagnosing Research Designs BLAIR, GRAEME COOPER, JASPER COPPOCK, ALEXANDER HUMPHREYS, MACARTAN Am Polit Sci Rev Article Researchers need to select high-quality research designs and communicate those designs clearly to readers. Both tasks are difficult. We provide a framework for formally “declaring” the analytically relevant features of a research design in a demonstrably complete manner, with applications to qualitative, quantitative, and mixed methods research. The approach to design declaration we describe requires defining a model of the world (M), an inquiry (I), adatastrategy(D), andananswerstrategy(A). Declaration of these features in code provides sufficient information for researchers and readers to use Monte Carlo techniques to diagnose properties such as power, bias, accuracy of qualitative causal inferences, and other “diagnosands.” Ex ante declarations can be used to improve designs and facilitate preregistration, analysis, and reconciliation of intended and actual analyses. Ex post declarations are useful for describing, sharing, reanalyzing, and critiquing existing designs. We provide open-source software, DeclareDesign, to implement the proposed approach. 2019-05-31 2019-08 /pmc/articles/PMC7449569/ /pubmed/32855557 http://dx.doi.org/10.1017/s0003055419000194 Text en This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
BLAIR, GRAEME
COOPER, JASPER
COPPOCK, ALEXANDER
HUMPHREYS, MACARTAN
Declaring and Diagnosing Research Designs
title Declaring and Diagnosing Research Designs
title_full Declaring and Diagnosing Research Designs
title_fullStr Declaring and Diagnosing Research Designs
title_full_unstemmed Declaring and Diagnosing Research Designs
title_short Declaring and Diagnosing Research Designs
title_sort declaring and diagnosing research designs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7449569/
https://www.ncbi.nlm.nih.gov/pubmed/32855557
http://dx.doi.org/10.1017/s0003055419000194
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