Matches in SemOpenAlex for { <https://semopenalex.org/work/W4290744339> ?p ?o ?g. }
- W4290744339 abstract "Planned missing survey data, for example stemming from split questionnaire designs are becoming increasingly common in survey research, making imputation indispensable to obtain reasonably analyzable data. However, these data can be difficult to impute due to low correlations, many predictors, and limited sample sizes to support imputation models. This paper presents findings from a Monte Carlo simulation, in which we investigate the accuracy of correlations after multiple imputation using different imputation methods and predictor set specifications based on data from the German Internet Panel (GIP). The results show that strategies that simplify the imputation exercise (such as predictive mean matching with dimensionality reduction or restricted predictor sets, linear regression models, or the multivariate normal model without transformation) perform well, while especially generalized linear models for categorical data, classification trees, and imputation models with many predictor variables lead to strong biases." @default.
- W4290744339 created "2022-08-09" @default.
- W4290744339 creator A5024895880 @default.
- W4290744339 creator A5071413535 @default.
- W4290744339 creator A5088945719 @default.
- W4290744339 date "2022-01-01" @default.
- W4290744339 modified "2023-10-18" @default.
- W4290744339 title "General-purpose imputation of planned missing data in social surveys: Different strategies and their effect on correlations" @default.
- W4290744339 cites W1513618424 @default.
- W4290744339 cites W1822348759 @default.
- W4290744339 cites W1972851018 @default.
- W4290744339 cites W1976251851 @default.
- W4290744339 cites W1979370357 @default.
- W4290744339 cites W1981131227 @default.
- W4290744339 cites W1989597713 @default.
- W4290744339 cites W1997241682 @default.
- W4290744339 cites W1999508687 @default.
- W4290744339 cites W2000521158 @default.
- W4290744339 cites W2025979859 @default.
- W4290744339 cites W2031668066 @default.
- W4290744339 cites W2043284092 @default.
- W4290744339 cites W2057777484 @default.
- W4290744339 cites W2058854776 @default.
- W4290744339 cites W2096555119 @default.
- W4290744339 cites W2097959846 @default.
- W4290744339 cites W2102252264 @default.
- W4290744339 cites W2109002515 @default.
- W4290744339 cites W2113559481 @default.
- W4290744339 cites W2115098571 @default.
- W4290744339 cites W2118502261 @default.
- W4290744339 cites W2119240586 @default.
- W4290744339 cites W2125291718 @default.
- W4290744339 cites W2127053344 @default.
- W4290744339 cites W2129030861 @default.
- W4290744339 cites W2133494987 @default.
- W4290744339 cites W2134843796 @default.
- W4290744339 cites W2140959043 @default.
- W4290744339 cites W2157235443 @default.
- W4290744339 cites W2160888843 @default.
- W4290744339 cites W2169076391 @default.
- W4290744339 cites W2417368995 @default.
- W4290744339 cites W2623886678 @default.
- W4290744339 cites W2765886208 @default.
- W4290744339 cites W2800968938 @default.
- W4290744339 cites W2891381594 @default.
- W4290744339 cites W3003667353 @default.
- W4290744339 cites W3091844591 @default.
- W4290744339 cites W3099639464 @default.
- W4290744339 cites W3102147710 @default.
- W4290744339 cites W3117978087 @default.
- W4290744339 cites W4206281252 @default.
- W4290744339 cites W4237171445 @default.
- W4290744339 cites W4242289937 @default.
- W4290744339 cites W4255287912 @default.
- W4290744339 doi "https://doi.org/10.1214/22-ss137" @default.
- W4290744339 hasPublicationYear "2022" @default.
- W4290744339 type Work @default.
- W4290744339 citedByCount "0" @default.
- W4290744339 crossrefType "journal-article" @default.
- W4290744339 hasAuthorship W4290744339A5024895880 @default.
- W4290744339 hasAuthorship W4290744339A5071413535 @default.
- W4290744339 hasAuthorship W4290744339A5088945719 @default.
- W4290744339 hasBestOaLocation W42907443391 @default.
- W4290744339 hasConcept C105795698 @default.
- W4290744339 hasConcept C124101348 @default.
- W4290744339 hasConcept C149782125 @default.
- W4290744339 hasConcept C161584116 @default.
- W4290744339 hasConcept C33923547 @default.
- W4290744339 hasConcept C41008148 @default.
- W4290744339 hasConcept C5274069 @default.
- W4290744339 hasConcept C58041806 @default.
- W4290744339 hasConcept C9357733 @default.
- W4290744339 hasConceptScore W4290744339C105795698 @default.
- W4290744339 hasConceptScore W4290744339C124101348 @default.
- W4290744339 hasConceptScore W4290744339C149782125 @default.
- W4290744339 hasConceptScore W4290744339C161584116 @default.
- W4290744339 hasConceptScore W4290744339C33923547 @default.
- W4290744339 hasConceptScore W4290744339C41008148 @default.
- W4290744339 hasConceptScore W4290744339C5274069 @default.
- W4290744339 hasConceptScore W4290744339C58041806 @default.
- W4290744339 hasConceptScore W4290744339C9357733 @default.
- W4290744339 hasIssue "none" @default.
- W4290744339 hasLocation W42907443391 @default.
- W4290744339 hasLocation W42907443392 @default.
- W4290744339 hasLocation W42907443393 @default.
- W4290744339 hasOpenAccess W4290744339 @default.
- W4290744339 hasPrimaryLocation W42907443391 @default.
- W4290744339 hasRelatedWork W124339703 @default.
- W4290744339 hasRelatedWork W1971356345 @default.
- W4290744339 hasRelatedWork W21744023 @default.
- W4290744339 hasRelatedWork W2431448603 @default.
- W4290744339 hasRelatedWork W252385730 @default.
- W4290744339 hasRelatedWork W2739123277 @default.
- W4290744339 hasRelatedWork W2963777145 @default.
- W4290744339 hasRelatedWork W3010658448 @default.
- W4290744339 hasRelatedWork W3195921219 @default.
- W4290744339 hasRelatedWork W3207602811 @default.
- W4290744339 hasVolume "16" @default.
- W4290744339 isParatext "false" @default.
- W4290744339 isRetracted "false" @default.