Principal components analysis: Difference between revisions
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In [[statistics]], '''principal components analysis''' was developed by Pearson in 1901 and may be used for analysis of a [[cohort study]].<ref name="Pearson1901">{{cite journal|url= |title=On lines and planes of closest fit to systems of points in space| journal=Philosophical Magazine |author=Pearson, K |authorlink= |coauthors= |date= |format= |work= |publisher= |pages= |language= |archiveurl= |archivedate= |quote= |year=1901|volume=2|issue=|pages=559–572|accessdate=|doi=}}</ref> The principal components analysis can only correct for confounding by independent variables that have been ''measured''. | In [[statistics]], '''principal components analysis''' was developed by Pearson in 1901 and may be used for analysis of a [[cohort study]].<ref name="Pearson1901">{{cite journal|url= |title=On lines and planes of closest fit to systems of points in space| journal=Philosophical Magazine |author=Pearson, K |authorlink= |coauthors= |date= |format= |work= |publisher= |pages= |language= |archiveurl= |archivedate= |quote= |year=1901|volume=2|issue=|pages=559–572|accessdate=|doi=}}</ref> The principal components analysis can only correct for confounding by independent variables that have been ''measured''. | ||
Latest revision as of 09:10, 12 December 2011
In statistics, principal components analysis was developed by Pearson in 1901 and may be used for analysis of a cohort study.[1] The principal components analysis can only correct for confounding by independent variables that have been measured.
Software
Software available for meta-analysis includes:
- R programming language:
- HSAUR2 interactive package with a chapter containing sample demonstrations, "Principal Component Analysis: The Olympic Heptathlon" in "A Handbook of Statistical Analyses Using R".[2]
References
- ↑ Pearson, K (1901). "On lines and planes of closest fit to systems of points in space". Philosophical Magazine 2: 559–572. [e]
- ↑ Torsten Hothorn; Everitt, Brian. CRAN - Package HSAUR, 2nd ed.