Bootstrap Statistical Inference
Examples and Evaluations for Political Science
Bibliographic Data
| ID | 6232565 |
|---|---|
| Authors | Christopher Z Mooney (0000-0002-2670-9160, corresponding author) |
| Year | 1996 |
| Volume | 40 |
| Issue | 2 |
| Pages | 570 |
| Publication date | 1996-05-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | American Journal of Political Science (JOURNAL) |
| Journal identifiers | ISSN: 0092-5853 • E-ISSN: 1540-5907 |
| Publisher | JSTOR (PUBLISHER) |
| DOI | 10.2307/2111639 |
| OpenAlex | W2079936392 |
| Language | EN |
| Citations received | 23 |
| References cited | 33 |
Theory: Bootstrapping is a nonparametric approach to statistical inference that relies on large amounts of computation rather than mathematical analysis and distributional assumptions of traditional parametric inference. It has been shown to provide asymptotically accurate inferences for a wide variety of statistics. Hypothesis: Bootstrapping may make more accurate inferences than the parametric approach under two general circumstances: 1) when the assumptions of parametric inference are not tenable, and 2) when no parametric alternative exists for a problem. Methods: Monte Carlo simulation is used to test the performance of bootstrap and parametric confidence intervals for both types of situations in which bootstrapping is hypothesized to be superior to parametric inference. A single data example is used to illustrate the use of the bootstrap: a seats/votes model of U.S. House elections from 1932 to 1988. Results: My central conclusions are that in the cases examined: 1) bootstrap confidence intervals are at least as good as the parametric confidence interval and sometimes better, 2) OLS parametric confidence intervals do not perform too badly when the model error is non-normal, especially as sample size increases, and 3) when no parametric alternative exists, the bootstrap provides a reasonable method of making statistical inferences
Bootstrapping (finance · Confidence distribution · Confidence interval · Econometrics · Inference · Nonparametric statistics · Parametric model · Parametric statistics · Sampling distribution · Statistical hypothesis testing · Statistical inference · Statistical theory · Statistics · Artificial Intelligence · Computer Science · Data Analysis with R · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods and Inference
Economic Interdependence and International Conflict
Choice of Personal Assistance Services Providers by Medicare Beneficiaries Using a Consumer-Directed Benefit
Impact of a Health Promotion Nurse Intervention on Disability and Health Care Costs Among Elderly Adults With Heart Conditions
Homophobia, economic precarity and the well-being of sexual and gender diverse people in a 153-country survey
Decision Trees and Random Forests
Media diversity and the analysis of qualitative variation
The Dimensions of Power in the European Union
Inequality in frontline communication
Urban representation through deliberation
Interest group PAC contributions and the 1992 regulation of cable television
A Political Explanation of Variations in Central Bank Independence
All Votes Are Not Created Equal
Kinder and gentler ministers in consensus democracies? Personality and the selection of government members
Measuring Bias and Uncertainty in Ideal Point Estimates via the Parametric Bootstrap
Bowling the state back in
From selective integration into selective implementation
Making the Most of Statistical Analyses
Corruption, Political Allegiances, and Attitudes Toward Government in Contemporary Democracies
Classificando regimes políticos utilizando análise de conglomerados
Visão além do alcance
How Ostrom's design principles apply to large-scale commons
Tiebout Sorting in Metropolitan Areas
Statistical Inference for Measures of Inequality With a Cross-National Bootstrap Application
Interpreting and Using Regression
The Jackknife, the Bootstrap and Other Resampling Plans
An Introduction to the Bootstrap
Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy
Better Bootstrap Confidence Intervals
Bootstrap Methods
A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
Estimation and inference in econometrics
Bootsreg
Assessing Sampling Variation Relative to Number-of-Factors Criteria
A SAS Macro for Jackknifing the Results of Discriminant Analyses
Direct and Indirect Effects
Integrating Alternative Approaches to the Study of Judicial Voting
Does Regulation Matter
Party Legislative Representation as a Function of Election Results
Legislative Representation and Party Vote in New Zealand
Congress, Social Movements and Public Opinion
The Cube Law and the Decomposed System
Nomination Choices
"Rebuttal to Jacobson's "New Evidence for Old Arguments
Patterns of Congressional Voting
Corporatism and Consensus Democracy in Eighteen Countries
Of Silicon and Political Science – Computationally Intensive Techniques of Statistical Estimation and Inference
Measuring Electoral Bias
Constituency Service and Incumbency Advantage
Discriminant analysis
The Relationship between Seats and Votes in Two-Party Systems
The unicorn, the normal curve, and other improbable creatures
The Swing Ratio and Game Theory
Are Congressional Committees Composed of Preference Outliers
Reformulating the Cube Law for Proportional Representation Elections
Bootstrapping Goodness-of-Fit Measures in Structural Equation Models
An Introduction to Bootstrap Methods
| Unique citing works | 23 |
|---|---|
| Citations per year | 0,82 |
| Citation span | 1998 - 2025 (28) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 23 |