Interpreting and Understanding Logits, Probits, and Other Nonlinear Probability Models
Dados Bibliográficos
| AUTOR(ES) | |
|---|---|
| AFILIAÇÃO(ÕES) | University of Oxford School of Anthropology and Museum Ethnography, Department of Anthropology, University of Copenhagen, Department of Sociology, University of Western Ontario, London, Ontario N6A 5C2, Canada |
| ANO | 2018 |
| TIPO | Artigo |
| PERIÓDICO | Annual Review of Sociology |
| ISSN | 0360-0572 |
| E-ISSN | 1545-2115 |
| EDITORA | Publisher 15279 |
| DOI | 10.1146/annurev-soc-073117-041429 |
| CITAÇÕES | 79 |
| ADICIONADO EM | 2025-08-18 |
| MD5 |
2f79535d24936824f4d6d9ccf5e2a189
|
Resumo
Methods textbooks in sociology and other social sciences routinely recommend the use of the logit or probit model when an outcome variable is binary, an ordered logit or ordered probit when it is ordinal, and a multinomial logit when it has more than two categories. But these methodological guidelines take little or no account of a body of work that, over the past 30 years, has pointed to problematic aspects of these nonlinear probability models and, particularly, to difficulties in interpreting their parameters. In this review, we draw on that literature to explain the problems, show how they manifest themselves in research, discuss the strengths and weaknesses of alternatives that have been suggested, and point to lines of further analysis.