How Data Imputation Affects Crash Modeling Results

How Data Imputation Affects Crash Modeling Results

Crash modification factors (CMF) are used to determine safety treatments for highways. These are based on estimates from correlations of road geometry attributes with crash frequency. These estimates are derived from models using datasets that may have missing data and analysts may choose how to com...

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Bibliographic Details
Main Authors: Yemi Adediji, Robert Noland
Format: Article
Language:English
Published: Network Design Lab
Series:Transport Findings
Online Access:http://transportfindings.scholasticahq.com/article/17386-how-data-imputation-affects-crash-modeling-results.pdf
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spelling doaj-1232e7220d6b42f1b5d0b2ff82d7fa5b2020-11-25T04:00:33ZengNetwork Design LabTransport Findings2652-0397How Data Imputation Affects Crash Modeling ResultsYemi AdedijiRobert NolandCrash modification factors (CMF) are used to determine safety treatments for highways. These are based on estimates from correlations of road geometry attributes with crash frequency. These estimates are derived from models using datasets that may have missing data and analysts may choose how to compensate for this. Using data from North Carolina, we examine changes in inferences associated with missing data by comparing models with full data sets with models where we omit vehicle kilometers traveled and impute the missing data. Results were mixed, showing notable changes for some variables. This could potentially lead to bad decisions in practice on how to improve road safety.http://transportfindings.scholasticahq.com/article/17386-how-data-imputation-affects-crash-modeling-results.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Yemi Adediji
Robert Noland
spellingShingle Yemi Adediji
Robert Noland
How Data Imputation Affects Crash Modeling Results
Transport Findings
author_facet Yemi Adediji
Robert Noland
author_sort Yemi Adediji
title How Data Imputation Affects Crash Modeling Results
title_short How Data Imputation Affects Crash Modeling Results
title_full How Data Imputation Affects Crash Modeling Results
title_fullStr How Data Imputation Affects Crash Modeling Results
title_full_unstemmed How Data Imputation Affects Crash Modeling Results
title_sort how data imputation affects crash modeling results
publisher Network Design Lab
series Transport Findings
issn 2652-0397
description Crash modification factors (CMF) are used to determine safety treatments for highways. These are based on estimates from correlations of road geometry attributes with crash frequency. These estimates are derived from models using datasets that may have missing data and analysts may choose how to compensate for this. Using data from North Carolina, we examine changes in inferences associated with missing data by comparing models with full data sets with models where we omit vehicle kilometers traveled and impute the missing data. Results were mixed, showing notable changes for some variables. This could potentially lead to bad decisions in practice on how to improve road safety.
url http://transportfindings.scholasticahq.com/article/17386-how-data-imputation-affects-crash-modeling-results.pdf
work_keys_str_mv AT yemiadediji howdataimputationaffectscrashmodelingresults
AT robertnoland howdataimputationaffectscrashmodelingresults
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