{"doi":"10.1002/9781119111931.ch104","title":"OLS (Linear) Regression","abstract":null,"journal":"The Encyclopedia of Research Methods in Criminology and Criminal Justice","year":2021,"id":626331,"datarank":0.6830815337400812,"base_score":4.553876891600541,"endowment":4.553876891600541,"self_citation_contribution":0.6830815337400812,"citation_network_contribution":0.0,"self_endowment_contribution":0.6830815337400812,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":94,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1620137,"name":"Alexander L. Burton","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"OLS (Linear) Regression","abstract":"Regression modeling allows researchers to examine the specific effects variables have on one another, net of the effects other variables. Although many types of regression frameworks exist, the most frequently used in criminal justice research are logistic regression techniques (example, binary logistic regression, ordinal logistic regression, and multinomial logistic regression) and ordinary least squares (OLS) regression. The latter, OLS, is the focus of this chapter. First, the chapter defines the ordinary least squares method. Second, it provides a practical guide with special attention paid to the data assumptions that must be met to conduct an OLS linear regression. Once the assumptions of the OLS regression framework have been met, a researcher can interpret their results with confidence. The chapter concludes with the statistics that should be interpreted in an OLS regression model output.","is_dataset_classified":null,"base_score":4.553876891600541,"endowment":4.553876891600541,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19910364","pmcid":null,"openalex_id":"https://openalex.org/W3193918736","authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2021,"count":1},{"year":2022,"count":6},{"year":2023,"count":4},{"year":2024,"count":24},{"year":2025,"count":37},{"year":2026,"count":22}],"oa_status":"closed","license":"http://doi.wiley.com/10.1002/tdm_license_1.1","oa_locations":[{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781119111931.ch104","host_type":"publisher"},{"url":"https://doi.org/10.1002/9781119111931.ch104","host_type":"journal"}],"fields_of_study":["Crime Patterns and Interventions","Animal Ecology and Behavior Studies","Fire effects on ecosystems"],"mesh_terms":[],"keywords":["Multinomial logistic regression","Regression diagnostic","Ordinary least squares","Logistic regression","Statistics","Cross-sectional regression","Econometrics","Proper linear model","Polynomial regression","Regression analysis","Binomial regression","Local regression","Mathematics","Linear regression","Regression"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Climate action"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-04T13:25:05.005551Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}