Assessing Fit Quality and Testing for Misspecification in Binary-Dependent Variable Models
Bibliographic Data
| ID | 7971089 |
|---|---|
| Authors | Justin E Esarey (0000-0002-6592-770X, Rice University, corresponding author), Justin Esarey, Andrew Pierce (0000-0001-5995-2469, Emory University) |
| Year | 2012 |
| Volume | 20 |
| Issue | 4 |
| Pages | 480-500 |
| Publication date | 2012-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Political Analysis (JOURNAL) |
| Journal identifiers | ISSN: 1047-1987 • E-ISSN: 1476-4989 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1093/pan/mps026 |
| OpenAlex | W2314155091 |
| Language | EN |
| Citations received | 2 |
| References cited | 28 |
In this article, we present a technique and critical test statistic for assessing the fit of a binary-dependent variable model (e.g., a logit or probit). We examine how closely a model's predicted probabilities match the observed frequency of events in the data set, and whether these deviations are systematic or merely noise. Our technique allows researchers to detect problems with a model's specification that obscure substantive understanding of the underlying data-generating process, such as missing interaction terms or unmodeled nonlinearities. We also show that these problems go undetected by the fit statistics most commonly used in political science
Binary number · Data set · Econometrics · Logit · Ordered probit · Probit · Probit model · Quality (philosophy · Set (abstract data type · Statistic · Statistical hypothesis testing · Statistics · Test statistic · Variable (mathematics · Computer Science · Electoral Systems and Political Participation · Mathematics · Political Conflict and Governance · Political Influence and Corporate Strategies
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| Unique citing works | 2 |
|---|---|
| Citations per year | 0,2 |
| Citation span | 2016 - 2021 (6) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 2 |