Path Analysis for Binary Random Variables
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| Title: | Path Analysis for Binary Random Variables |
|---|---|
| Language: | English |
| Authors: | Raggi, Martina (ORCID |
| Source: | Sociological Methods & Research. 2023 52(4):1883-1915. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 33 |
| Publication Date: | 2023 |
| Document Type: | Journal Articles Reports - Evaluative |
| Descriptors: | Path Analysis, Student Attitudes, Museums, Error of Measurement, Foreign Countries, Graphs, Regression (Statistics) |
| Geographic Terms: | Italy |
| DOI: | 10.1177/00491241211031260 |
| ISSN: | 0049-1241 1552-8294 |
| Abstract: | The decomposition of the overall effect of a treatment into direct and indirect effects is here investigated with reference to a recursive system of binary random variables. We show how, for the single mediator context, the marginal effect measured on the log odds scale can be written as the sum of the indirect and direct effects plus a residual term that vanishes under some specific conditions. We then extend our definitions to situations involving multiple mediators and address research questions concerning the decomposition of the total effect when some mediators on the pathway from the treatment to the outcome are marginalized over. Connections to the counterfactual definitions of the effects are also made. Data coming from an encouragement design on students' attitude to visit museums in Florence, Italy, are reanalyzed. The estimates of the defined quantities are reported together with their standard errors to compute p values and form confidence intervals. |
| Abstractor: | As Provided |
| Entry Date: | 2023 |
| Accession Number: | EJ1397548 |
| Database: | ERIC |
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| Abstract: | The decomposition of the overall effect of a treatment into direct and indirect effects is here investigated with reference to a recursive system of binary random variables. We show how, for the single mediator context, the marginal effect measured on the log odds scale can be written as the sum of the indirect and direct effects plus a residual term that vanishes under some specific conditions. We then extend our definitions to situations involving multiple mediators and address research questions concerning the decomposition of the total effect when some mediators on the pathway from the treatment to the outcome are marginalized over. Connections to the counterfactual definitions of the effects are also made. Data coming from an encouragement design on students' attitude to visit museums in Florence, Italy, are reanalyzed. The estimates of the defined quantities are reported together with their standard errors to compute p values and form confidence intervals. |
|---|---|
| ISSN: | 0049-1241 1552-8294 |
| DOI: | 10.1177/00491241211031260 |
