Quantitative Approaches to Comparative Analyses
Data properties and their implications for theory, measurement and modelling
Bibliographic Data
| ID | 12869457 |
|---|---|
| Authors | Robert Neumann (0000-0001-6728-4288, Technische Universität Dresden, corresponding author), Peter Graeff (0000-0003-1110-0384, Christian-Albrechts-Universität zu Kiel) |
| Year | 2015 |
| Volume | 14 |
| Issue | 4 |
| Pages | 385-393 |
| Publication date | 2015-11-06 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | European Political Science (JOURNAL) |
| Journal identifiers | ISSN: 1680-4333 • E-ISSN: 1682-0983 |
| Publisher | Palgrave Macmillan (PUBLISHER • GB) |
| DOI | 10.1057/eps.2015.59 |
| OpenAlex | W2163082419 |
| Language | EN |
| Citations received | 1 |
| References cited | 28 |
While there is an abundant use of macro data in the social sciences, little attention is given to the sources or the construction of these data. Owing to the restricted amount of indices or items, researchers most often apply the ‘available data at hand’. Since the opportunities to analyse data are constantly increasing and the availability of macro indicators is improving as well, one may be enticed to incorporate even qualitatively inferior indicators for the sake of statistically significant results. The pitfalls of applying biased indicators or using instruments with unknown methodological characteristics are biased estimates, false statistical inferences and, as one potential consequence, the derivation of misleading policy recommendations. This Special Issue assembles contributions that attempt to stimulate the missing debate about the criteria of assessing aggregate data and their measurement properties for comparative analyses
Aggregate (composite · Aggregate data · Comparative politics · Data science · Econometrics · Economics · Macro · Management science · Political science · Politics · Positive economics · Statistics · Computer Science · Corruption and Economic Development · Income, Poverty, and Inequality · Law · Mathematics · Qualitative Comparative Analysis Research
Designing Social Inquiry
Bayesian Analysis for the Social Sciences
Philosophy and the practice of Bayesian statistics
The Statistical Crisis in Science
Structural Equations with Latent Variables
Social Science Methodology
Assessing the Quality of Quality Measures of Democracy
Separating Dirty War From Dirty Peace
Studying Media Events in the European Social Surveys Across Research Designs, Countries, Time, Issues, and Outcomes
Measurement and Analysis of Industrial Relations Aggregates
The Construction of Human Rights
Testing for Measurement Invariance by Detecting Local Misspecification and an Illustration Across Online and Paper-and-Pencil Samples
Vulnerability and Compensation
Response to ‘What do the Worldwide Governance Indicators Measure?’
What Do the Worldwide Governance Indicators Measure
Method Bias in Comparative Research
Two Multilevel Modeling Techniques for Analyzing Comparative Longitudinal Survey Datasets
Introduction
Improving Data Quality
From Statistical Nuisances to Serious Modeling
Convergent and discriminant validation by the multitrait-multimethod matrix
Big Data
Liberal Democracy Series I, 1972-1988
Measurement Validity
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2025 - 2025 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |