{"created":"2023-05-15T12:19:15.735917+00:00","id":9462,"links":{},"metadata":{"_buckets":{"deposit":"a915c000-1df9-40c0-807b-47466d59c130"},"_deposit":{"created_by":1,"id":"9462","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"9462"},"status":"published"},"_oai":{"id":"oai:kansai-u.repo.nii.ac.jp:00009462","sets":["528:1385:1386:1411"]},"author_link":["18905","18906"],"item_10_alternative_title_20":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"Exploring the Patterns of Skill Development by Mixture Growth Modeling: Using the Batting Average Data on Professional Baseball Players"}]},"item_10_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2008-12-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicPageEnd":"37","bibliographicPageStart":"17","bibliographicVolumeNumber":"40","bibliographic_titles":[{"bibliographic_title":"関西大学社会学部紀要"}]}]},"item_10_description_4":{"attribute_name":"概要","attribute_value_mlt":[{"subitem_description":"　Reviewing latent growth modeling for longitudinal data and some results using this methodology on career development, mixture modeling methodologies were introduced for identifying clusters of individuals following similar developmental trajectories. For the latent growth model analysis by Amos and the groupbased trajectory model analysis using SAS Traj procedure, the batting average records of Japanese professional baseball players over ten years were selected from the published offi cial records. Results of latent growth modeling demonstrated that the quadratic form trajectory model fi t the data well. Six subgroups were also clustered by the same quadratic form using the Traj. Findings of these analyses were discussed with particular reference to the utility of the group-based trajectory modeling of mixture model methodology for analyzing career development processes.\n　縦断的データへの潜在成長モデルとこの方法論を使ったキャリア発達についての結果を概観しながら、混合モデリングの方法論を、類似した発達軌跡に従う個人のクラスタを特定するために、紹介した。Amosによる潜在成長モデル分析とSAS Trajプロシジャを使った集団ベースの軌跡モデル分析のために、10年間を越える記録を持つ日本のプロ野球選手の打撃成績記録を公開されている公式記録から取り出した。潜在成長モデルの結果は、2次形式軌跡モデルがデータにうまく適合することを示した。6集団が、また、TRAJを使って、同じ2次形式によってクラスタ化された。これらの分析からの見いだしたことを、混合モデル方法論の集団ベースの軌跡モデル化の有用性をキャリア発達過程の解析と関連づけて議論した。","subitem_description_type":"Other"}]},"item_10_full_name_3":{"attribute_name":"著者別名","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"18906","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Shimizu, Kazuaki"}]}]},"item_10_publisher_34":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"関西大学社会学部"}]},"item_10_source_id_10":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00046982","subitem_source_identifier_type":"NCID"}]},"item_10_source_id_8":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"02876817","subitem_source_identifier_type":"ISSN"}]},"item_10_version_type_17":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"清水, 和秋"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-05-22"}],"displaytype":"detail","filename":"KU-1100SK-20081200-02.pdf","filesize":[{"value":"529.1 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"KU-1100SK-20081200-02.pdf","url":"https://kansai-u.repo.nii.ac.jp/record/9462/files/KU-1100SK-20081200-02.pdf"},"version_id":"b9fdc415-3c5a-45f9-b34f-3e01553e0207"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"latent growth model","subitem_subject_scheme":"Other"},{"subitem_subject":"mixture modeling","subitem_subject_scheme":"Other"},{"subitem_subject":"group-based trajectory model","subitem_subject_scheme":"Other"},{"subitem_subject":"baseball","subitem_subject_scheme":"Other"},{"subitem_subject":"career development","subitem_subject_scheme":"Other"},{"subitem_subject":"trajectory","subitem_subject_scheme":"Other"},{"subitem_subject":"潜在成長モデル","subitem_subject_scheme":"Other"},{"subitem_subject":"混合モデル","subitem_subject_scheme":"Other"},{"subitem_subject":"集団ベース軌跡モデル","subitem_subject_scheme":"Other"},{"subitem_subject":"野球","subitem_subject_scheme":"Other"},{"subitem_subject":"キャリア発達","subitem_subject_scheme":"Other"},{"subitem_subject":"軌跡","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"混合モデルによる熟達パターンの探索－プロ野球選手の熟達の軌跡を例として－","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"混合モデルによる熟達パターンの探索－プロ野球選手の熟達の軌跡を例として－"}]},"item_type_id":"10","owner":"1","path":["1411"],"pubdate":{"attribute_name":"公開日","attribute_value":"2010-12-24"},"publish_date":"2010-12-24","publish_status":"0","recid":"9462","relation_version_is_last":true,"title":["混合モデルによる熟達パターンの探索－プロ野球選手の熟達の軌跡を例として－"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-05-15T19:35:18.369360+00:00"}