FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2023546680> ?p ?o ?g. }

• W2023546680 endingPage "337" @default.
• W2023546680 startingPage "317" @default.
• W2023546680 abstract "The hierarchical linear model (HLM) is now commonly accepted as a useful modeling approach for multilevel data resulting from randomized field experiments. When multiple outcomes of interest exist, a multivariate extension of the conventional univariate HLM offers advantages over the usual application of separate HLM analyses for each of the outcomes. In this article, the authors review these advantages, discuss the device that allows the univariate HLM procedure to model multiple outcomes, and present a series of multivariate models that would be useful in addressing typical questions in field experiments. In addition to the multivariate multilevel versions of basic analysis of variance (ANOVA) or analysis of covariance (ANCOVA) designs, the authors present more complex models that allow the testing of moderation and mediation of the treatment effect. The various analyses are illustrated with computer generated data for a hypothetical scenario." @default.
• W2023546680 created "2016-06-24" @default.
• W2023546680 creator A5054667381 @default.
• W2023546680 creator A5058369088 @default.
• W2023546680 date "2007-07-01" @default.
• W2023546680 modified "2023-10-16" @default.
• W2023546680 title "Multivariate Hierarchical Linear Modeling in Randomized Field Experiments" @default.
• W2023546680 cites W1587990062 @default.
• W2023546680 cites W1592263067 @default.
• W2023546680 cites W1964090882 @default.
• W2023546680 cites W1972102668 @default.
• W2023546680 cites W1976876708 @default.
• W2023546680 cites W1980909828 @default.
• W2023546680 cites W1983760254 @default.
• W2023546680 cites W1983769299 @default.
• W2023546680 cites W1999352976 @default.
• W2023546680 cites W2003258289 @default.
• W2023546680 cites W2008053863 @default.
• W2023546680 cites W2027386447 @default.
• W2023546680 cites W2031878292 @default.
• W2023546680 cites W2051951888 @default.
• W2023546680 cites W2061980801 @default.
• W2023546680 cites W2072582001 @default.
• W2023546680 cites W2078171930 @default.
• W2023546680 cites W2079257116 @default.
• W2023546680 cites W2080705323 @default.
• W2023546680 cites W2113168655 @default.
• W2023546680 cites W2117278087 @default.
• W2023546680 cites W2120897808 @default.
• W2023546680 cites W2121944882 @default.
• W2023546680 cites W2123568515 @default.
• W2023546680 cites W2134654456 @default.
• W2023546680 cites W2153114676 @default.
• W2023546680 cites W2324392187 @default.
• W2023546680 cites W2801119256 @default.
• W2023546680 cites W2936971519 @default.
• W2023546680 cites W6874264 @default.
• W2023546680 cites W3041876382 @default.
• W2023546680 doi "https://doi.org/10.3200/jexe.75.4.317-338" @default.
• W2023546680 hasPublicationYear "2007" @default.
• W2023546680 type Work @default.
• W2023546680 sameAs 2023546680 @default.
• W2023546680 citedByCount "36" @default.
• W2023546680 countsByYear W20235466802012 @default.
• W2023546680 countsByYear W20235466802013 @default.
• W2023546680 countsByYear W20235466802014 @default.
• W2023546680 countsByYear W20235466802015 @default.
• W2023546680 countsByYear W20235466802016 @default.
• W2023546680 countsByYear W20235466802017 @default.
• W2023546680 countsByYear W20235466802018 @default.
• W2023546680 countsByYear W20235466802019 @default.
• W2023546680 countsByYear W20235466802020 @default.
• W2023546680 countsByYear W20235466802021 @default.
• W2023546680 countsByYear W20235466802022 @default.
• W2023546680 countsByYear W20235466802023 @default.
• W2023546680 crossrefType "journal-article" @default.
• W2023546680 hasAuthorship W2023546680A5054667381 @default.
• W2023546680 hasAuthorship W2023546680A5058369088 @default.
• W2023546680 hasConcept C105795698 @default.
• W2023546680 hasConcept C119340705 @default.
• W2023546680 hasConcept C124101348 @default.
• W2023546680 hasConcept C144986985 @default.
• W2023546680 hasConcept C149782125 @default.
• W2023546680 hasConcept C161584116 @default.
• W2023546680 hasConcept C163175372 @default.
• W2023546680 hasConcept C178650346 @default.
• W2023546680 hasConcept C192424360 @default.
• W2023546680 hasConcept C199163554 @default.
• W2023546680 hasConcept C202444582 @default.
• W2023546680 hasConcept C33923547 @default.
• W2023546680 hasConcept C38180746 @default.
• W2023546680 hasConcept C41008148 @default.
• W2023546680 hasConcept C53059260 @default.
• W2023546680 hasConcept C93225998 @default.
• W2023546680 hasConcept C9652623 @default.
• W2023546680 hasConceptScore W2023546680C105795698 @default.
• W2023546680 hasConceptScore W2023546680C119340705 @default.
• W2023546680 hasConceptScore W2023546680C124101348 @default.
• W2023546680 hasConceptScore W2023546680C144986985 @default.
• W2023546680 hasConceptScore W2023546680C149782125 @default.
• W2023546680 hasConceptScore W2023546680C161584116 @default.
• W2023546680 hasConceptScore W2023546680C163175372 @default.
• W2023546680 hasConceptScore W2023546680C178650346 @default.
• W2023546680 hasConceptScore W2023546680C192424360 @default.
• W2023546680 hasConceptScore W2023546680C199163554 @default.
• W2023546680 hasConceptScore W2023546680C202444582 @default.
• W2023546680 hasConceptScore W2023546680C33923547 @default.
• W2023546680 hasConceptScore W2023546680C38180746 @default.
• W2023546680 hasConceptScore W2023546680C41008148 @default.
• W2023546680 hasConceptScore W2023546680C53059260 @default.
• W2023546680 hasConceptScore W2023546680C93225998 @default.
• W2023546680 hasConceptScore W2023546680C9652623 @default.
• W2023546680 hasIssue "4" @default.
• W2023546680 hasLocation W20235466801 @default.
• W2023546680 hasOpenAccess W2023546680 @default.
• W2023546680 hasPrimaryLocation W20235466801 @default.
• W2023546680 hasRelatedWork W2040288080 @default.
• W2023546680 hasRelatedWork W2053542176 @default.

• next