{"doi":"10.5351/kjas.2012.25.3.521","title":"Semi-Partial Canonical Correlation Biplot","abstract":null,"journal":"Korean Journal of Applied Statistics","year":2012,"id":689091,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"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":1777814,"name":"Yong-Seok Choi","orcid":null,"position":1,"is_corresponding":false},{"id":1800238,"name":"Sang-Min Shin","orcid":null,"position":2,"is_corresponding":false},{"id":1800237,"name":"Bo-Hui Lee","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Semi-Partial Canonical Correlation Biplot","abstract":"Simple canonical correlation biplot is a graphical method to investigate two sets of variables and observations in simple canonical correlation analysis. If we consider the set of covariate variables that linearly affects two sets of variables, we can apply the partial canonical correlation biplot in partial canonical correlation analysis that removes the linear effect of the set of covariate variables on two sets of variables. On the other hand, we consider the set of covariate variables that linearly affect one set of variables but not the other. In this case, if we apply the simple or partial canonical correlation biplot, we cannot clearly interpret other two sets of variables. Therefore, in this study, we will apply the semi-partial canonical correlation analysis of Timm (2002) and remove the linear effect of the set of covariate variables on one set of variables but not the other. And we suggest the semi-partial canonical correlation biplot for interpreting the semi-partial canonical correlation analysis. In addition, we will compare shapes and shape the variabilities of the simple, partial and semi-partial canonical correlation biplots using a procrustes analysis.","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"21097893","pmcid":null,"openalex_id":"https://openalex.org/W2003363096","authors":[],"funders":[],"total_grants":0,"fwci":0.0,"citation_percentile":0.10358306,"influential_citations":0,"citation_trend":[],"oa_status":"bronze","license":null,"oa_locations":[{"url":"http://koreascience.or.kr:80/article/JAKO201222350107329.pdf","host_type":"journal"},{"url":"http://koreascience.or.kr:80/article/JAKO201222350107329.pdf","host_type":"publisher"},{"url":"http://ocean.kisti.re.kr/downfile/crosscheck/kss/JAKO201222350107329.pdf","host_type":"publisher"},{"url":"https://doi.org/10.5351/kjas.2012.25.3.521","host_type":"journal"}],"fields_of_study":["Genetics and Plant Breeding","Spectroscopy and Chemometric Analyses","Genetic and phenotypic traits in livestock"],"mesh_terms":[],"keywords":["Biplot","Canonical correlation","Mathematics","Covariate","Canonical analysis","Partial correlation","Correlation","Canonical correspondence analysis","Set (abstract data type)","Simple correlation","Simple (philosophy)","Statistics","Regression analysis","Computer science"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Reduced inequalities"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-19T22:19:42.537621Z","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":[]}