Matches in SemOpenAlex for { <https://semopenalex.org/work/W3184681775> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W3184681775 endingPage "1181" @default.
- W3184681775 startingPage "1165" @default.
- W3184681775 abstract "Summary There has been increased interest in using prior information in statistical analyses. For example, in rare diseases, it can be difficult to establish treatment efficacy based solely on data from a prospective study due to low sample sizes. To overcome this issue, an informative prior to the treatment effect may be elicited. We develop a novel extension of the conjugate prior of Chen and Ibrahim (2003) that enables practitioners to elicit a prior prediction for the mean response for generalized linear models, treating the prediction as random. We refer to the hierarchical prior as the hierarchical prediction prior (HPP). For independent and identically distributed settings and the normal linear model, we derive cases for which the hyperprior is a conjugate prior. We also develop an extension of the HPP in situations where summary statistics from a previous study are available. The HPP allows for discounting based on the quality of individual level predictions, and simulation results suggest that, compared to the conjugate prior and the power prior, the HPP efficiency gains (e.g., lower mean squared error) where predictions are incompatible with the data. An efficient Monte Carlo Markov chain algorithm is developed. Applications illustrate that inferences under the HPP are more robust to prior-data conflict compared to selected nonhierarchical priors." @default.
- W3184681775 created "2021-08-02" @default.
- W3184681775 creator A5056166869 @default.
- W3184681775 creator A5056185563 @default.
- W3184681775 creator A5078399867 @default.
- W3184681775 date "2022-06-30" @default.
- W3184681775 modified "2023-09-23" @default.
- W3184681775 title "A hierarchical prior for generalized linear models based on predictions for the mean response" @default.
- W3184681775 cites W1844985714 @default.
- W3184681775 cites W1937505006 @default.
- W3184681775 cites W1975386608 @default.
- W3184681775 cites W2035460524 @default.
- W3184681775 cites W2143143555 @default.
- W3184681775 cites W2166992787 @default.
- W3184681775 cites W3193090929 @default.
- W3184681775 cites W4229681654 @default.
- W3184681775 cites W4230730227 @default.
- W3184681775 doi "https://doi.org/10.1093/biostatistics/kxac022" @default.
- W3184681775 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35770800" @default.
- W3184681775 hasPublicationYear "2022" @default.
- W3184681775 type Work @default.
- W3184681775 sameAs 3184681775 @default.
- W3184681775 citedByCount "0" @default.
- W3184681775 crossrefType "journal-article" @default.
- W3184681775 hasAuthorship W3184681775A5056166869 @default.
- W3184681775 hasAuthorship W3184681775A5056185563 @default.
- W3184681775 hasAuthorship W3184681775A5078399867 @default.
- W3184681775 hasBestOaLocation W31846817752 @default.
- W3184681775 hasConcept C105795698 @default.
- W3184681775 hasConcept C107673813 @default.
- W3184681775 hasConcept C111350023 @default.
- W3184681775 hasConcept C122123141 @default.
- W3184681775 hasConcept C124101348 @default.
- W3184681775 hasConcept C126322002 @default.
- W3184681775 hasConcept C129848803 @default.
- W3184681775 hasConcept C141513077 @default.
- W3184681775 hasConcept C144986985 @default.
- W3184681775 hasConcept C149782125 @default.
- W3184681775 hasConcept C163175372 @default.
- W3184681775 hasConcept C168743327 @default.
- W3184681775 hasConcept C177769412 @default.
- W3184681775 hasConcept C26004113 @default.
- W3184681775 hasConcept C33923547 @default.
- W3184681775 hasConcept C41008148 @default.
- W3184681775 hasConcept C53059260 @default.
- W3184681775 hasConcept C71924100 @default.
- W3184681775 hasConcept C95190672 @default.
- W3184681775 hasConceptScore W3184681775C105795698 @default.
- W3184681775 hasConceptScore W3184681775C107673813 @default.
- W3184681775 hasConceptScore W3184681775C111350023 @default.
- W3184681775 hasConceptScore W3184681775C122123141 @default.
- W3184681775 hasConceptScore W3184681775C124101348 @default.
- W3184681775 hasConceptScore W3184681775C126322002 @default.
- W3184681775 hasConceptScore W3184681775C129848803 @default.
- W3184681775 hasConceptScore W3184681775C141513077 @default.
- W3184681775 hasConceptScore W3184681775C144986985 @default.
- W3184681775 hasConceptScore W3184681775C149782125 @default.
- W3184681775 hasConceptScore W3184681775C163175372 @default.
- W3184681775 hasConceptScore W3184681775C168743327 @default.
- W3184681775 hasConceptScore W3184681775C177769412 @default.
- W3184681775 hasConceptScore W3184681775C26004113 @default.
- W3184681775 hasConceptScore W3184681775C33923547 @default.
- W3184681775 hasConceptScore W3184681775C41008148 @default.
- W3184681775 hasConceptScore W3184681775C53059260 @default.
- W3184681775 hasConceptScore W3184681775C71924100 @default.
- W3184681775 hasConceptScore W3184681775C95190672 @default.
- W3184681775 hasFunder F4320337361 @default.
- W3184681775 hasIssue "4" @default.
- W3184681775 hasLocation W31846817751 @default.
- W3184681775 hasLocation W31846817752 @default.
- W3184681775 hasLocation W31846817753 @default.
- W3184681775 hasLocation W31846817754 @default.
- W3184681775 hasOpenAccess W3184681775 @default.
- W3184681775 hasPrimaryLocation W31846817751 @default.
- W3184681775 hasRelatedWork W1495673277 @default.
- W3184681775 hasRelatedWork W1699863832 @default.
- W3184681775 hasRelatedWork W1991247336 @default.
- W3184681775 hasRelatedWork W2006031679 @default.
- W3184681775 hasRelatedWork W2033200554 @default.
- W3184681775 hasRelatedWork W2059348506 @default.
- W3184681775 hasRelatedWork W2596700956 @default.
- W3184681775 hasRelatedWork W2801157135 @default.
- W3184681775 hasRelatedWork W3125715954 @default.
- W3184681775 hasRelatedWork W4318457042 @default.
- W3184681775 hasVolume "23" @default.
- W3184681775 isParatext "false" @default.
- W3184681775 isRetracted "false" @default.
- W3184681775 magId "3184681775" @default.
- W3184681775 workType "article" @default.