Matches in SemOpenAlex for { <https://semopenalex.org/work/W2521853008> ?p ?o ?g. }
Showing items 1 to 83 of
83
with 100 items per page.
- W2521853008 abstract "As is commonly known, ordinary linear regression falls short when the predictor variables are highly correlated with each other, because in that case, the estimates for the regression weights tend to be unstable. Principal Covariates Regression (PCovR) was developed by De Jong & Kiers (1991) as a solution to this problem. PCovR combines the main ideas behind Principal Component Analysis(PCA) and regression. Like PCA, PCovR reduces the variables to a few components and, like regression, it predicts the criterion variables, but using the components as predictor variables. Specifically, PCovR minimizes the following criterion: α ‖X−TPX‖ + (1 − α) ‖Y −TPY‖, where X and Y are the scores on, respectively, the predictor and the criterion variables, α is the weighting parameter, which indicates the extent to which the reconstruction of the predictor scores and the criterion scores are emphasized, T contains the scores of the observations on the components, PX holds the loadings of the predictor variables on the components, and PY are the regression weights of the components when predicting the criterion variables. Although PCovR is potentially a very interesting method (e.g., there are strong relations with exploratory SEM; Asparouhov & Muthen, 2009), it is rarely used. This might be because the estimates for the regression weights PY display rotational freedom. Another issue is the optimal value of the weighting parameter α. In this paper, based on extensive simulations, we make some recommendations on how to deal with the rotational freedom and how to select the value of α." @default.
- W2521853008 created "2016-09-30" @default.
- W2521853008 creator A5024742630 @default.
- W2521853008 creator A5062580529 @default.
- W2521853008 creator A5065025082 @default.
- W2521853008 creator A5091274668 @default.
- W2521853008 date "2011-01-01" @default.
- W2521853008 modified "2023-09-27" @default.
- W2521853008 title "Principal covariates regression: How to weight and rotate?" @default.
- W2521853008 cites W1488808450 @default.
- W2521853008 cites W2040890982 @default.
- W2521853008 hasPublicationYear "2011" @default.
- W2521853008 type Work @default.
- W2521853008 sameAs 2521853008 @default.
- W2521853008 citedByCount "0" @default.
- W2521853008 crossrefType "journal-article" @default.
- W2521853008 hasAuthorship W2521853008A5024742630 @default.
- W2521853008 hasAuthorship W2521853008A5062580529 @default.
- W2521853008 hasAuthorship W2521853008A5065025082 @default.
- W2521853008 hasAuthorship W2521853008A5091274668 @default.
- W2521853008 hasConcept C105795698 @default.
- W2521853008 hasConcept C119043178 @default.
- W2521853008 hasConcept C120068334 @default.
- W2521853008 hasConcept C121332964 @default.
- W2521853008 hasConcept C126838900 @default.
- W2521853008 hasConcept C149782125 @default.
- W2521853008 hasConcept C152877465 @default.
- W2521853008 hasConcept C183115368 @default.
- W2521853008 hasConcept C208081375 @default.
- W2521853008 hasConcept C27438332 @default.
- W2521853008 hasConcept C32224588 @default.
- W2521853008 hasConcept C33923547 @default.
- W2521853008 hasConcept C35519122 @default.
- W2521853008 hasConcept C48921125 @default.
- W2521853008 hasConcept C62520636 @default.
- W2521853008 hasConcept C71924100 @default.
- W2521853008 hasConcept C74887250 @default.
- W2521853008 hasConcept C83546350 @default.
- W2521853008 hasConceptScore W2521853008C105795698 @default.
- W2521853008 hasConceptScore W2521853008C119043178 @default.
- W2521853008 hasConceptScore W2521853008C120068334 @default.
- W2521853008 hasConceptScore W2521853008C121332964 @default.
- W2521853008 hasConceptScore W2521853008C126838900 @default.
- W2521853008 hasConceptScore W2521853008C149782125 @default.
- W2521853008 hasConceptScore W2521853008C152877465 @default.
- W2521853008 hasConceptScore W2521853008C183115368 @default.
- W2521853008 hasConceptScore W2521853008C208081375 @default.
- W2521853008 hasConceptScore W2521853008C27438332 @default.
- W2521853008 hasConceptScore W2521853008C32224588 @default.
- W2521853008 hasConceptScore W2521853008C33923547 @default.
- W2521853008 hasConceptScore W2521853008C35519122 @default.
- W2521853008 hasConceptScore W2521853008C48921125 @default.
- W2521853008 hasConceptScore W2521853008C62520636 @default.
- W2521853008 hasConceptScore W2521853008C71924100 @default.
- W2521853008 hasConceptScore W2521853008C74887250 @default.
- W2521853008 hasConceptScore W2521853008C83546350 @default.
- W2521853008 hasLocation W25218530081 @default.
- W2521853008 hasOpenAccess W2521853008 @default.
- W2521853008 hasPrimaryLocation W25218530081 @default.
- W2521853008 hasRelatedWork W1034674023 @default.
- W2521853008 hasRelatedWork W1567620106 @default.
- W2521853008 hasRelatedWork W1859657261 @default.
- W2521853008 hasRelatedWork W1981297600 @default.
- W2521853008 hasRelatedWork W2002605354 @default.
- W2521853008 hasRelatedWork W2010237043 @default.
- W2521853008 hasRelatedWork W2071090551 @default.
- W2521853008 hasRelatedWork W2072242739 @default.
- W2521853008 hasRelatedWork W2115218557 @default.
- W2521853008 hasRelatedWork W2126661394 @default.
- W2521853008 hasRelatedWork W2765318274 @default.
- W2521853008 hasRelatedWork W2792940999 @default.
- W2521853008 hasRelatedWork W2998808478 @default.
- W2521853008 hasRelatedWork W3015020719 @default.
- W2521853008 hasRelatedWork W3022629739 @default.
- W2521853008 hasRelatedWork W3098893258 @default.
- W2521853008 hasRelatedWork W3141305146 @default.
- W2521853008 hasRelatedWork W3199271261 @default.
- W2521853008 hasRelatedWork W97929189 @default.
- W2521853008 hasRelatedWork W2183605469 @default.
- W2521853008 isParatext "false" @default.
- W2521853008 isRetracted "false" @default.
- W2521853008 magId "2521853008" @default.
- W2521853008 workType "article" @default.