{"title":"Event review: Using multivariate analyses to interpret lithic variability: Contributions and limitations","authors":"A. Leplongeon, E. Garcea","doi":"10.2218/jls.6666","DOIUrl":null,"url":null,"abstract":"A selection of papers presented at the Special Session 8 ‘Using multivariate analyses to interpret lithic variability: Contributions and limitations’ held during the 2018 MetroArchaeo conference (22-24 October 2018, Cassino, Italy) is published in the Journal of Lithic Studies. Multivariate statistical analyses are increasingly used to discern patterns of variability in archaeological materials and help with their interpretation. Commonly used ones include Principal Component Analysis, Multiple Correspondence Analysis, Discriminant Analysis, Multiple Regression, General Linear Model, or Cluster Analysis, applied in various contexts of study: geometric morphometrics, spatial analysis or inter-assemblage comparisons.","PeriodicalId":44072,"journal":{"name":"Journal of Lithic Studies","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2021-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Lithic Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2218/jls.6666","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"ARCHAEOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
A selection of papers presented at the Special Session 8 ‘Using multivariate analyses to interpret lithic variability: Contributions and limitations’ held during the 2018 MetroArchaeo conference (22-24 October 2018, Cassino, Italy) is published in the Journal of Lithic Studies. Multivariate statistical analyses are increasingly used to discern patterns of variability in archaeological materials and help with their interpretation. Commonly used ones include Principal Component Analysis, Multiple Correspondence Analysis, Discriminant Analysis, Multiple Regression, General Linear Model, or Cluster Analysis, applied in various contexts of study: geometric morphometrics, spatial analysis or inter-assemblage comparisons.