Using the Specification Curve to Teach Spatial Data Analysis and Explore Geographic Uncertainties

Autor/inn/en	Kedron, Peter; Quick, Matthew; Hilgendorf, Zach; Sachdeva, Mehak
Titel	Using the Specification Curve to Teach Spatial Data Analysis and Explore Geographic Uncertainties
Quelle	In: Journal of Geography in Higher Education, 46 (2022) 2, S.304-314 (11 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Kedron, Peter) ORCID (Quick, Matthew) ORCID (Hilgendorf, Zach) ORCID (Sachdeva, Mehak)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0309-8265
DOI	10.1080/03098265.2021.1901076
Schlagwörter	Geography Instruction; Data Analysis; Meta Analysis; Decision Making; Computer Software; Instructional Materials; Teaching Methods; Regression (Statistics); Predictor Variables; Visual Aids; Geographic Information Systems; Information Science; Housing; Goodness of Fit; Costs; Ownership; Generalization; Publications; Bias; Maryland (Baltimore) + Suchen Sie Ihr Suchwort? Geography education; Geography lessons; Geografieunterricht; Auswertung; Meta-analysis; Metaanalyse; Decision-making; Entscheidungsfindung; Lehrmaterial; Lehrmittel; Unterrichtsmedien; Teaching method; Lehrmethode; Unterrichtsmethode; Regression; Regressionsanalyse; Prädiktor; Anschauungsmaterial; Informationswissenschaft; Unterkunft; Cost; Kosten; Eigentum
Abstract	Educational materials focused on spatial data analysis often feature mathematical descriptions of methods and step-by-step instructions of software tools, but infrequently discuss the set of decisions involved in specifying a statistical model. Failing to consider model specification may lead to specification searching, or the process of repeating analyses to obtain results that meet the criteria thought to be required for publication, and the disproportionate reporting of false-positive results in the academic literature. This article proposes that the specification curve -- a meta-analytical technique that visualizes the specifications and results from a large set of justifiable and plausible statistical models -- be used as a pedagogical tool to teach (spatial) data analysis and explore the geographic uncertainties that arise when specifying and interpreting spatial regression models. An example specification curve that focuses on two common specification decisions in a spatial regression model, specifically selecting predictor variables and constructing the spatial weight matrix, is illustrated. Strategies for using the specification curve in educational contexts to develop analytical plans, reflect on the generalizability of research findings, and highlight issues of replicability and publication bias are proposed. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01