{"created":"2024-10-09T05:15:23.234685+00:00","id":2001929,"links":{},"metadata":{"_buckets":{"deposit":"027c6ad9-cd45-4c2a-99dc-72354dbc5956"},"_deposit":{"created_by":10,"id":"2001929","owner":"10","owners":[10],"pid":{"revision_id":0,"type":"depid","value":"2001929"},"status":"published"},"_oai":{"id":"oai:kansai-u.repo.nii.ac.jp:02001929","sets":["528:1385:1386:1728448557905"]},"author_link":["18563"],"control_number":"2001929","item_10_alternative_title_20":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"Hypothetical Models of Factorial Invariance by Structure Equation Modeling: Estimation Method of the Invariant Means and Variances for Standardization of Psychological Test","subitem_alternative_title_language":"en"}]},"item_10_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2024-09-30","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicPageEnd":"94","bibliographicPageStart":"45","bibliographicVolumeNumber":"56","bibliographic_titles":[{"bibliographic_title":"関西大学社会学部紀要","bibliographic_titleLang":"ja"}]}]},"item_10_description_4":{"attribute_name":"概要","attribute_value_mlt":[{"subitem_description":"受検者に対する心理検査や尺度の公平性を評価する重要な側面の1つは、研究対象のグループ間での因子的不変性の確認である。因子的不変性について多数の仮説モデルが研究者によって提案されている。これらのモデルは、通常、因子パターン行列、因子間の共分散行列、独自性の対角行列を含む共分散構造モデルと、切片ベクトルと因子得点の平均ベクトルからなる平均構造モデルから構成される。しかしながら、これらの行列とベクトルがグループ間で不変であることを保証するために課される制約に関して、これらの仮説モデルの間には微妙な不一致がある。特に，因子間の共分散行列をどのように扱うかについては，見解が分かれている。この論文では、仮想モデルを構成する要素は次のように指定した。共分散構造の設定は、次の枠組みで定義した。1) 因子パターン(不変)、因子間共分散(不変)、独自性(不変)。2) 因子パターン(不変)、因子間共分散(不変でない)、独自性(不変)。3)  因子パターン(不変)、因子間共分散(不変)、独自性(不変でない)。4) 因子パターン(不変)、因子間共分散(不変でない)、独自性(不変でない)。同様に、平均構造の枠組みは次のように指定した。a) 切片(不変)、因子平均(不変)。b) 切片(不変でない)、因子平均(不変)。c) 切片(不変)、因子平均(不変でない)。d) 切片(不変でない)、因子平均(不変でない)。その結果、合計16の種類の仮想モデルを記述できた。さらに、応用的研究として、矢田部・ギルフォード性格検査の因子的不変性モデルを構造方程式モデリングにより検討した。この分析から、因子パターン行列、因子間共分散行列、および独自性対角行列は不変であり、特定の切片と因子平均は不変ではないこと示すことができた。最後に、独自性間の共分散を組み込むことにより、モデルの全体的な適合度がより良くなったことを報告した。","subitem_description_language":"ja","subitem_description_type":"Other"},{"subitem_description":"One important aspect of evaluating the fairness of a psychological test or scale for examinees is confirming factorial invariance across the groups being studied. Researchers have proposed numerous hypothetical models of factorial invariance. These models typically consist of two components: the covariance structure model and the mean structure model. The covariance structure model includes the factor pattern matrix, the covariance matrix among factors, and the diagonal matrix of uniqueness. The mean structure model consists of the intercept vector and the mean vector of factor scores. However, there are subtle discrepancies among these hypothetical models regarding the constraints imposed to ensure that these matrices and vectors remain invariant across groups. Notably, there are differing perspectives on how to handle the covariance matrix among factors. In this paper, the components of a hypothetical model were specified as follows. The covariance structure settings were defined by the following schemes: 1. factor pattern (invariant), factor covariance (invariant), uniqueness (invariant), 2. factor pattern (invariant), factor covariance (not invariant), uniqueness (invariant), 3.factor pattern (invariant), factor covariance (invariant), uniqueness (not invariant), and 4. factor pattern (invariant), factor covariance (not invariant), uniqueness (not invariant). Similarly, the mean structure schemes were specified as: a. intercept (invariant), factor means (invariant), b. intercept (not invariant), factor means (invariant), c. intercept (invariant), factor means (not invariant), and d. intercept (not invariant), factor means (not invariant). Consequently, a total of sixteen distinct hypothetical models were delineated. Furthermore, as an applied study, the factorial invariance models of the Yatabe-Guilford Personality Test were scrutinized using structural equation modeling. The analysis revealed that the factor pattern matrix, factor covariance matrix, and uniqueness diagonal matrix were invariant, while certain intercepts and factor means were not invariant. Finally, it was reported that by incorporating covariance among uniqueness, the overall model fit was improved.","subitem_description_language":"en","subitem_description_type":"Other"}]},"item_10_identifier_registration":{"attribute_name":"ID登録","attribute_value_mlt":[{"subitem_identifier_reg_text":"10.32286/0002001929","subitem_identifier_reg_type":"JaLC"}]},"item_10_publisher_34":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"関西大学社会学部","subitem_publisher_language":"ja"}]},"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":"PISSN"}]},"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_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"清水, 和秋","creatorNameLang":"ja"},{"creatorName":"Shimizu, Kazuaki","creatorNameLang":"en"}],"familyNames":[{"familyName":"清水","familyNameLang":"ja"},{"familyName":"Shimizu","familyNameLang":"en"}],"givenNames":[{"givenName":"和秋","givenNameLang":"ja"},{"givenName":"Kazuaki","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"18563","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"40140248","nameIdentifierScheme":"e-Rad_Researcher","nameIdentifierURI":"https://nrid.nii.ac.jp/ja/nrid/1000040140248"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2024-10-10"}],"displaytype":"detail","filename":"KU-1100-20240930-02.pdf","filesize":[{"value":"982 KB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://kansai-u.repo.nii.ac.jp/record/2001929/files/KU-1100-20240930-02.pdf"},"version_id":"9a6c5d25-daae-4081-971a-3ce296abcf55"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"因子的不変性","subitem_subject_language":"ja","subitem_subject_scheme":"Other"},{"subitem_subject":"構造方程式モデリング","subitem_subject_language":"ja","subitem_subject_scheme":"Other"},{"subitem_subject":"多群分析","subitem_subject_language":"ja","subitem_subject_scheme":"Other"},{"subitem_subject":"共分散構造","subitem_subject_language":"ja","subitem_subject_scheme":"Other"},{"subitem_subject":"平均構造","subitem_subject_language":"ja","subitem_subject_scheme":"Other"},{"subitem_subject":"心理尺度","subitem_subject_language":"ja","subitem_subject_scheme":"Other"},{"subitem_subject":"factorial invariance","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"structural equation modeling","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"multi-group analysis","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"covariance structure","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"mean structure","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"psychological scale","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"関西大学","subitem_subject_language":"ja","subitem_subject_scheme":"Other"},{"subitem_subject":"Kansai University","subitem_subject_language":"en","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":"構造方程式モデリングによる因子的不変性の仮説的モデル : 心理検査の基準化のための平均と分散の推定","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"構造方程式モデリングによる因子的不変性の仮説的モデル : 心理検査の基準化のための平均と分散の推定","subitem_title_language":"ja"}]},"item_type_id":"10","owner":"10","path":["1728448557905"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2024-10-09"},"publish_date":"2024-10-09","publish_status":"0","recid":"2001929","relation_version_is_last":true,"title":["構造方程式モデリングによる因子的不変性の仮説的モデル : 心理検査の基準化のための平均と分散の推定"],"weko_creator_id":"10","weko_shared_id":-1},"updated":"2025-03-03T07:21:09.718618+00:00"}