| LDR | | 02102nam u200397 4500 |
| 001 | | 000000422096 |
| 005 | | 20190215165842 |
| 008 | | 181129s2016 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438136106 |
| 035 | |
▼a (MiAaPQ)AAI10903785 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 624 |
| 100 | 1 |
▼a Wood, Jonathan S. |
| 245 | 10 |
▼a Causal Inference in Traffic Safety Research: Comparison of the Empirical Bayes and Propensity Scores-Potential Outcomes Methods. |
| 260 | |
▼a [S.l.]:
▼b The Pennsylvania State University.,
▼c 2016. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2016. |
| 300 | |
▼a 211 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
| 502 | 1 |
▼a Thesis (Ph.D.)--The Pennsylvania State University, 2016. |
| 520 | |
▼a Accurate estimation of safety treatment effectiveness is an important part of the transportation engineering and research profession. Transportation engineering practitioners use safety treatment effect estimates to identify countermeasures that |
| 520 | |
▼a In this thesis, the counterfactuals framework is applied to the empirical Bayes before-after and propensity scores-potential outcomes methods to describe how to generalize the results of both methods to the population of potential entities that |
| 520 | |
▼a Finally, based on these findings, guidelines for developing crash modification factors are provided. Based on these guidelines, a flowchart for determining which analysis method to use is developed. |
| 590 | |
▼a School code: 0176. |
| 650 | 4 |
▼a Civil engineering. |
| 650 | 4 |
▼a Statistics. |
| 690 | |
▼a 0543 |
| 690 | |
▼a 0463 |
| 710 | 20 |
▼a The Pennsylvania State University.
▼b Civil and Environmental Engineering. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0176 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2016 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000742
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |