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The Estimation of Correlation Matrix from Data Having Missing Values. Kaiser, Javaid [microform]
The Estimation of Correlation Matrix from Data Having Missing Values. Kaiser, Javaid [microform]
상세정보
- 자료유형
- 마이크로피시
- 언어부호
- 본문언어 - English
- 청구기호
- 서명/저자
- The Estimation of Correlation Matrix from Data Having Missing Values. : Kaiser, Javaid - [microform]
- 발행사항
- 형태사항
- 19; 1
- 총서명
- ERIC Reports
- 주기사항
- 19p.; Paper presented at the Islamic Countries Conference on Statistical Sciences (4th, Lahore, Pakistan, August 27-31, 1994).
- 초록/해제
- 요약A Monte Carlo study was conducted to compare the efficiency of Listwise deletion, Pairwise deletion, Allvalue, and Samemean methods in estimating the correlation matrix from data that had randomly occurring missing values. The four methods were compared in a 3x3x4 factorial design representing sample size, proportion of incomplete records in the sample, and the number of missing values per record. Each sample represented an N x 8 data matrix. The Pairwise method was found best in estimating the correlation matrix under all experimental conditions except when the incomplete records had 50 of values missing. In this condition, Listwise deletion was considered a better choice. Allvalue and Samemean methods performed exactly the same way under all experimental conditions, but were found less efficient than the Pairwise method. One table, three figures. (Contains 12 references.) (Au
- 복제주기
- Microfiche. . Springfield, VA : ERIC Document Reproduction Service. . microfiches ; 11×15 cm.
- 일반주제명
- 키워드
- 기타저자
MARC
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■001PCUL00365628
■002ED380473
■00520020812091724
■007heuumu---buua
■008980928s1994 us b 000 0 eng d
■040 ▼apcul
■0410 ▼aEnglish
■090 ▼a370.78▼bE68
■24500▼aThe Estimation of Correlation Matrix from Data Having Missing Values.▼cKaiser, Javaid▼h[microform]
■260 ▼aU.S.; VirginiaM▼cAug 94
■300 ▼a19; 1
■440 0▼aERIC Reports
■500 ▼a19p.; Paper presented at the Islamic Countries Conference on Statistical Sciences (4th, Lahore, Pakistan, August 27-31, 1994).
■520 ▼aA Monte Carlo study was conducted to compare the efficiency of Listwise deletion, Pairwise deletion, Allvalue, and Samemean methods in estimating the correlation matrix from data that had randomly occurring missing values. The four methods were compared in a 3x3x4 factorial design representing sample size, proportion of incomplete records in the sample, and the number of missing values per record. Each sample represented an N x 8 data matrix. The Pairwise method was found best in estimating the correlation matrix under all experimental conditions except when the incomplete records had 50 of values missing. In this condition, Listwise deletion was considered a better choice. Allvalue and Samemean methods performed exactly the same way under all experimental conditions, but were found less efficient than the Pairwise method. One table, three figures. (Contains 12 references.) (Au
■533 ▼aMicrofiche.▼bSpringfield, VA▼cERIC Document Reproduction Service.▼emicrofiches ; 11×15 cm.
■650 4▼xEducation
■653 ▼aComparative Analysis▼aCorrelation▼aEstimation (Mathematics)▼aMatrices▼aMonte Carlo Methods▼aResearch Methodology▼aSample Size▼aStatistical Analysis▼aMissing Data
■7001 ▼aKaiser, Javaid
■999 ▼a150; 143
