Using simulations to interpret results from logit, probit, and other nonlinear models (Record no. 32616)
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| fixed length control field | 02127naa a2200181uu 4500 |
| 001 - CONTROL NUMBER | |
| control field | 0042615575137 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20190211171235.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 100426s2009 xx ||||gr |0|| 0 eng d |
| 999 ## - SYSTEM CONTROL NUMBERS (KOHA) | |
| Koha Dewey Subclass [OBSOLETE] | PHL2MARC21 1.1 |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | ZELNER, Bennet A. |
| 9 (RLIN) | 39706 |
| 245 10 - TITLE STATEMENT | |
| Title | Using simulations to interpret results from logit, probit, and other nonlinear models |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Bognor Regis : |
| Name of publisher, distributor, etc. | Wiley-Blackwell, |
| Date of publication, distribution, etc. | December 2009 |
| 520 3# - SUMMARY, ETC. | |
| Summary, etc. | In a recent issue of this journal, Glenn Hoetker proposes that researchers improve the interpretation and presentation of logit and probit results by reporting the marginal effects of key independent variables at theoretically interesting or empirically relevant values of the other independent variables in the model, and also by presenting results graphically (Hoetker, 2007: 335, 337). In this research note, I suggest an alternative approach for achieving this objective: reporting differences in predicted probabilities associated with discrete changes in key independent variable values. This intuitive approach to interpretation is especially useful when the theoretically interesting or empirically relevant changes in independent variables values are not very small, and also for models that contain interaction terms (or higher-order terms such as quadratics). Although the graphical presentations recommended by Hoetker implicitly embody this approach, they typically fail to include appropriate measures of statistical significance, and may therefore lead to erroneous conclusions. In order to calculate such measures, I recommend and demonstrate an intuitive simulation-based approach to statistical interpretation, developed by King et al. (2000), that has gained widespread adherence in the field of political science. Throughout the article, I provide a running example based on research that has previously appeared in the Strategic Management Journal. |
| 773 08 - HOST ITEM ENTRY | |
| Title | Strategic Management Journal |
| Related parts | 30, 12, p. 1335-1348 |
| Place, publisher, and date of publication | Bognor Regis : Wiley-Blackwell, December 2009 |
| International Standard Serial Number | ISSN 01432095 |
| Record control number | |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Periódico |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| -- | 20100426 |
| Operator's initials, OID (RLIN) | 1557^b |
| Cataloger's initials, CIN (RLIN) | Daiane |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| -- | 20100428 |
| Operator's initials, OID (RLIN) | 1655^b |
| Cataloger's initials, CIN (RLIN) | Carolina |
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