{"created":"2023-05-15T12:25:50.329286+00:00","id":18463,"links":{},"metadata":{"_buckets":{"deposit":"f5bee92a-7808-46b5-8a3b-bb2308285c0d"},"_deposit":{"created_by":1,"id":"18463","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"18463"},"status":"published"},"_oai":{"id":"oai:kansai-u.repo.nii.ac.jp:00018463","sets":["528:1385:1386:2485"]},"author_link":["18576","43906"],"item_10_alternative_title_20":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"Monte Carlo Confirmatory Factor Analysis Study for the Data Sets of Normal Distribution, 5-Point Scale, 4-Point Scale, and 3-Point Scale "}]},"item_10_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1996-03-30","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicPageEnd":"198","bibliographicPageStart":"179","bibliographicVolumeNumber":"27","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":"構造方程式モデルの適合度統計量のふるまいを検討するために，EQS（Bentler，1995）のカテゴリー化でのシミュレーションオプションで発生させた3種類の標本数（100，200そして400）の4種類の尺度（連続正規分布，5件法，4件法そして3件法）に，検証的因子分析法を適用した。因子分析のモデル値とLISREL（Jöreskog and Sörbom，1993a）の最尤法で推定した値との乖離を，適合度指標のふるまいと比較するために計算した。この研究の実験計画内での10試行から計算された平均値から，次の結果を得た。(1)独立適合度指標（GFIとAGFI）は構造方程式モデルの評価では使用できない。(2)増分変化量適合度指標（NFI，PNFI，NNFIとIFI）のふるまいはよい。(3)構造方程式モデルの分析での適切な標本の数は，4件法と5件法では，200あるいはそれ以上である。(4)3件法では，400あるいはそれ以上の標本の数が適切である。","subitem_description_type":"Other"},{"subitem_description":"To evaluate the behavior of the goodness of fit statistics for structural equation modeling (SEM), a Monte Carlo confirmatory factor analysis study was conducted for three levels of sample size (100, 200, and 400) with the four levels of scale (continuous normal distribution, 5-point scale 4-point scale, and 3-point scale), generated by EQS (Bentler, 1995) using the simulation option-with categorization. The discrepancies between the values of the factor analysis model and the estimates by the Maximum Likelihood method of LISREL (Jöreskog and Sörbom, 1993a) were calculated for comparison with the behavior of the goodness of fit indices. The results from the means of ten trials in each experimental design of this study indicated that: (1) stand-alone fit indices (GFI and AGFI) were not acceptable for the evaluation of SEM; (2) incremental fit indices (NFI, PNFI, NNFI and IFI) performed better; (3) in the analysis of SEM, a suitable sample size was 200 or more for 4-point and 5-point scale; and (4) an acceptable sample size for 3-point scale was 400 or more. ","subitem_description_type":"Other"}]},"item_10_full_name_3":{"attribute_name":"著者別名","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"43906","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":[{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"","affiliationNameIdentifierScheme":"ISNI","affiliationNameIdentifierURI":"http://www.isni.org/isni/"}],"affiliationNames":[{"affiliationName":"","affiliationNameLang":"ja"}]}],"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":"18576","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"40140248","nameIdentifierScheme":"e-Rad","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_date","date":[{"dateType":"Available","dateValue":"2021-02-01"}],"displaytype":"detail","filename":"KU-1100-19960330-08.pdf","filesize":[{"value":"2.1 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"KU-1100-19960330-08.pdf","url":"https://kansai-u.repo.nii.ac.jp/record/18463/files/KU-1100-19960330-08.pdf"},"version_id":"19b7dc7e-9044-4fcb-b5dc-6f13aa6b4076"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"構造方程式モデル","subitem_subject_scheme":"Other"},{"subitem_subject":"適合性指標","subitem_subject_scheme":"Other"},{"subitem_subject":"リッカートスケール","subitem_subject_scheme":"Other"},{"subitem_subject":"因子分析","subitem_subject_scheme":"Other"},{"subitem_subject":"標本数","subitem_subject_scheme":"Other"},{"subitem_subject":"モンテカルロ","subitem_subject_scheme":"Other"},{"subitem_subject":"EQS","subitem_subject_scheme":"Other"},{"subitem_subject":"LISREL","subitem_subject_scheme":"Other"},{"subitem_subject":"structural equation model","subitem_subject_scheme":"Other"},{"subitem_subject":"goodness of fit index","subitem_subject_scheme":"Other"},{"subitem_subject":"Likert-type scale","subitem_subject_scheme":"Other"},{"subitem_subject":"factor analysis","subitem_subject_scheme":"Other"},{"subitem_subject":"number of samples","subitem_subject_scheme":"Other"},{"subitem_subject":"Monte Carlo","subitem_subject_scheme":"Other"},{"subitem_subject":"関西大学","subitem_subject_scheme":"Other"},{"subitem_subject":"Kansai University","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":"検証的因子分析のモンテカルロ・シミュレ-ション : 正規分布・5件法・4件法・3件法の乱数データへの適用","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"検証的因子分析のモンテカルロ・シミュレ-ション : 正規分布・5件法・4件法・3件法の乱数データへの適用"}]},"item_type_id":"10","owner":"1","path":["2485"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-02-01"},"publish_date":"2021-02-01","publish_status":"0","recid":"18463","relation_version_is_last":true,"title":["検証的因子分析のモンテカルロ・シミュレ-ション : 正規分布・5件法・4件法・3件法の乱数データへの適用"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2025-01-15T01:10:15.995597+00:00"}