ログイン
言語:

WEKO3

  • トップ
  • ランキング
To
lat lon distance
To

Field does not validate



インデックスリンク

インデックスツリー

メールアドレスを入力してください。

WEKO

One fine body…

WEKO

One fine body…

アイテム

{"_buckets": {"deposit": "a90182e8-b4c1-48f2-a952-df71c858fcd4"}, "_deposit": {"id": "2266", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "2266"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00002266", "sets": ["396"]}, "item_9_alternative_title_19": {"attribute_name": "その他の言語のタイトル", "attribute_value_mlt": [{"subitem_alternative_title": "EXPLORATORY FACTOR ANALYSIS OF MULTISET DATA"}]}, "item_9_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "1985-12-20", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "93", "bibliographicPageStart": "75", "bibliographicVolumeNumber": "32", "bibliographic_titles": [{"bibliographic_title": "名古屋大學教育學部紀要. 教育心理学科"}]}]}, "item_9_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "A new exploratory method, multiset factor analysis, which factor analyzes data consisting of several sets of variables related to different domains or levels was proposed. Basic equations of this method are written as [numerical formula] where R_\u003ckk\u0027\u003e is n_k by n_k correlation matrix between variables of set k and k\u0027, A_k is n_k by q_k factor loading matrix for set k, S_\u003ckk\u0027\u003e is q_k by q_\u003ck\u0027\u003e correlation matrix between factor scores satisfying [numerical formula] and D_\u003ckk\u0027\u003e is diagonal matrix including unique variances when k = k\u0027, and zero matrix when k ≠ k\u0027 An alternating least squares algorithm is formulated. It assumes that [numerical formula] and [numerical formula] where L_k is diagonal and positive definite. Then following three equations [numerical formula] [numerical formula] and [numerical formula] are alternated until convergence is reached. Final solutions satisfying (2) are obtained through the transformations [numerical formula] and [numerical formula] This algorithm is a natural extension of ordinary principal factor method. A questionnaire data collected from housewives in Aichi prefecture was analyzed by this method. lt consists of four sets, - buying behavior, attitude for buying, need for information and confidence for the various media. A factor which could not be found by separate factor analysis was derived in the first set and interesting relations between the factor and factors of other sets were revealed.", "subitem_description_type": "Abstract"}]}, "item_9_description_5": {"attribute_name": "内容記述", "attribute_value_mlt": [{"subitem_description": "国立情報学研究所で電子化したコンテンツを使用している。", "subitem_description_type": "Other"}]}, "item_9_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/3689"}]}, "item_9_identifier_registration": {"attribute_name": "ID登録", "attribute_value_mlt": [{"subitem_identifier_reg_text": "10.18999/bulfep.32.75", "subitem_identifier_reg_type": "JaLC"}]}, "item_9_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "名古屋大学教育学部"}]}, "item_9_select_15": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_select_item": "publisher"}]}, "item_9_source_id_7": {"attribute_name": "ISSN(print)", "attribute_value_mlt": [{"subitem_source_identifier": "03874796", "subitem_source_identifier_type": "ISSN"}]}, "item_9_text_14": {"attribute_name": "フォーマット", "attribute_value_mlt": [{"subitem_text_value": "application/pdf"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "村上, 隆"}], "nameIdentifiers": [{"nameIdentifier": "6077", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "MURAKAMI, Takashi"}], "nameIdentifiers": [{"nameIdentifier": "6078", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2018-02-16"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "KJ00000725981.pdf", "filesize": [{"value": "1.4 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 1400000.0, "url": {"label": "KJ00000725981.pdf", "url": "https://nagoya.repo.nii.ac.jp/record/2266/files/KJ00000725981.pdf"}, "version_id": "07725007-aaa7-4561-bb23-a0d1545fb80c"}]}, "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": "多集合データのための探索的因子分析", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "多集合データのための探索的因子分析"}]}, "item_type_id": "9", "owner": "1", "path": ["396"], "permalink_uri": "https://doi.org/10.18999/bulfep.32.75", "pubdate": {"attribute_name": "公開日", "attribute_value": "2006-01-06"}, "publish_date": "2006-01-06", "publish_status": "0", "recid": "2266", "relation": {}, "relation_version_is_last": true, "title": ["多集合データのための探索的因子分析"], "weko_shared_id": null}
  1. A200 教育学部/教育発達科学研究科
  2. A200b 紀要
  3. 名古屋大學教育學部紀要. 教育心理学科
  4. 32

多集合データのための探索的因子分析

https://doi.org/10.18999/bulfep.32.75
https://doi.org/10.18999/bulfep.32.75
974b3fd0-f9ad-45b4-bede-e55cbba6f011
名前 / ファイル ライセンス アクション
KJ00000725981.pdf KJ00000725981.pdf (1.4 MB)
Item type 紀要論文 / Departmental Bulletin Paper(1)
公開日 2006-01-06
タイトル
タイトル 多集合データのための探索的因子分析
その他のタイトル
その他のタイトル EXPLORATORY FACTOR ANALYSIS OF MULTISET DATA
著者 村上, 隆

× 村上, 隆

WEKO 6077

村上, 隆

Search repository
MURAKAMI, Takashi

× MURAKAMI, Takashi

WEKO 6078

MURAKAMI, Takashi

Search repository
抄録
内容記述 A new exploratory method, multiset factor analysis, which factor analyzes data consisting of several sets of variables related to different domains or levels was proposed. Basic equations of this method are written as [numerical formula] where R_<kk'> is n_k by n_k correlation matrix between variables of set k and k', A_k is n_k by q_k factor loading matrix for set k, S_<kk'> is q_k by q_<k'> correlation matrix between factor scores satisfying [numerical formula] and D_<kk'> is diagonal matrix including unique variances when k = k', and zero matrix when k ≠ k' An alternating least squares algorithm is formulated. It assumes that [numerical formula] and [numerical formula] where L_k is diagonal and positive definite. Then following three equations [numerical formula] [numerical formula] and [numerical formula] are alternated until convergence is reached. Final solutions satisfying (2) are obtained through the transformations [numerical formula] and [numerical formula] This algorithm is a natural extension of ordinary principal factor method. A questionnaire data collected from housewives in Aichi prefecture was analyzed by this method. lt consists of four sets, - buying behavior, attitude for buying, need for information and confidence for the various media. A factor which could not be found by separate factor analysis was derived in the first set and interesting relations between the factor and factors of other sets were revealed.
内容記述タイプ Abstract
内容記述
内容記述 国立情報学研究所で電子化したコンテンツを使用している。
内容記述タイプ Other
出版者
出版者 名古屋大学教育学部
言語
言語 jpn
資源タイプ
資源 http://purl.org/coar/resource_type/c_6501
タイプ departmental bulletin paper
ID登録
ID登録 10.18999/bulfep.32.75
ID登録タイプ JaLC
ISSN(print)
収録物識別子タイプ ISSN
収録物識別子 03874796
書誌情報 名古屋大學教育學部紀要. 教育心理学科

巻 32, p. 75-93, 発行日 1985-12-20
フォーマット
application/pdf
著者版フラグ
値 publisher
URI
識別子 http://hdl.handle.net/2237/3689
識別子タイプ HDL
戻る
0
views
See details
Views

Versions

Ver.1 2021-03-01 21:23:56.018070
Show All versions

Share

Mendeley Twitter Facebook Print Addthis

Cite as

エクスポート

OAI-PMH
  • OAI-PMH JPCOAR
  • OAI-PMH DublinCore
  • OAI-PMH DDI
Other Formats
  • JSON
  • BIBTEX

Confirm


Powered by WEKO3


Powered by WEKO3