Missing, Biased, and Unrepresentative

The Quantitative Analysis of Multisource Biographical Data

Datos Bibliográficos

ID11253643
AutoresGidon Cohen (0000-0002-9899-5389, University of Salford, autor de correspondencia)
Año2002
Volumen35
Número4
Páginas166-176
Fecha de publicación2002-01-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaHistorical Methods A Journal of Quantitative and Interdisciplinary History (JOURNAL)
Identificadores de la revistaISSN: 0161-5440 • E-ISSN: 1940-1906
EditorialInforma UK Limited (PUBLISHER • GB)
DOI10.1080/01615440209601206
OpenAlexW2015315121
IdiomaEN
Citas recibidas6
Referencias citadas25

With the growth in interest in collective biography as a historical technique, many predominantly qualitative historians find themselves faced with large amounts of information. These data, collected from a variety of sources, are often highly irregular, making statistical analysis extremely problematic. Current practice is to ignore these problems and proceed with quantitative analysis suitable only for much more regular data. It is argued that a more satisfactory approach is to ascertain and directly confront the difficulties of analyzing such information. The three central problems are identified as missing data, systematic bias, and the lack of a representative sample. Using a practical example, the author explores the relationship between gender, the family, and political socialization within the Communist Party of Great Britain and shows how each of the issues can be dealt with in turn. The author first distinguishes truly missing data from “negative information,” which commonly appears to be missing in historical sources. He then stratifies the data to remove systematic biases relating to the issue at hand. Finally, he divides the sample into different populations, on the basis of the sources from which individuals are known, and compares the results obtained to examine whether his conclusions appear to depend on quirks of populations contained in the sources. These ideas open a new range of sources to quantitative analysis and raise the possibility of allowing new types of evidence to count in historical inquiry

Data science · Epistemology · Missing data · Political science · Politics · Quantitative analysis (chemistry · Sample (material · Social science · Socialization · Sociology · Statistics · Variety (cybernetics · Computer Science · Electoral Systems and Political Participation · Law · Mathematics