The Process of Political Development
An Illustrative Use of a Strategy for Regression in the Presence of Multicollinearity
Bibliographic Data
| ID | 2331291 |
|---|---|
| Authors | John Deegan (0000-0001-9190-8142, Rice University, corresponding author) |
| Year | 1975 |
| Volume | 3 |
| Issue | 4 |
| Pages | 384-415 |
| Publication date | 1975-05-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sociological Methods & Research (JOURNAL) |
| Journal identifiers | ISSN: 0049-1241 • E-ISSN: 1552-8294 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/004912417500300402 |
| OpenAlex | W2011959240 |
| Language | EN |
| Citations received | 10 |
| References cited | 13 |
Although a number of investigators have attempted to identify empirically a process of political development, substantial controversy still surrounds a determination of the causal factors involved. It is my contention that this state of affairs is the result of inadequacies inherent in traditional techniques of causal modeling, and aggravated when multicollinear variables are involved. To resolve this problem I first review a technique capable of reducing the confounding effects of multicollinearity. I then illustrate use of this technique, as well as a strategy for inferring causal relationships, by means of a reanalysis of published data used to construct models of political development. The strategy for causal inference utilized herein is derived from knowledge of the effects of model specification errors. On the basis of these findings a new causal model of political development, which is both theoretically and empirically consistent, is presented
Causal analysis · Causal inference · Causal model · Cognitive psychology · Confounding · Construct (python library) · Econometrics · Economics · Inference · Machine learning · Multicollinearity · Political science · Politics · Positive economics · Process (computing) · Regression analysis · Statistics · Artificial Intelligence · Computer Science · Law · Mathematics · Political Conflict and Governance · Psychology · Qualitative Comparative Analysis Research
Ridge Regression as a Technique for Analyzing Models with Multicollinearity
On the Occurrence of Standardized Regression Coefficients Greater Than One
Economic conditions, marital status, and the timing of first births
Ratio Variables in Aggregate Data Analysis
A Note On Ridge Regression
An Examination of an Ecological Model of Neighborhood Change, Which Employs a Biased Estimation Technique
Using secondary analysis for quosi-experimental research
Collinearity, Ridge Regression, and Investigator Judgment
Decreasing Multicollinearity
Optimal Bias in Ridge Regression Approaches To Multicollinearity
Ridge Regression
Socio-Economic Development and Political Democracy
Problems in Path Analysis and Causal Inference
Some Social Requisites of Democracy
Causal Inferences, Closed Populations, and Measures of Association
Toward a Communications Theory of Democratic Political Development
Some Conditions of Democracy
Political Development and Lerner's Theory
Specification error in causal models
| Unique citing works | 10 |
|---|---|
| Citations per year | 0,2 |
| Citation span | 1976 - 1989 (14) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 8 |