Augmenting Data With Published Results in Bayesian Linear Regression
| Autor: | De Leeuw, C., Klugkist, I.G., Methodology and statistics for the behavioural and social sciences, Afd methoden en statistieken |
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| Přispěvatelé: | Methodology and statistics for the behavioural and social sciences, Afd methoden en statistieken |
| Rok vydání: | 2012 |
| Předmět: |
Statistics and Probability
General linear model Proper linear model Computer science Data Science Linear model Experimental and Cognitive Psychology Regression analysis General Medicine Arts and Humanities (miscellaneous) Bayesian multivariate linear regression Linear regression Statistics Bayesian linear regression Regression diagnostic |
| Zdroj: | Multivariate Behavioral Research, 47, 3, pp. 369-391 Multivariate Behavioral Research, 47, 369-391 Multivariate Behavioral Research, 47(3), 369. Psychology Press Ltd |
| ISSN: | 0027-3171 |
| Popis: | In most research, linear regression analyses are performed without taking into account published results (i.e., reported summary statistics) of similar previous studies. Although the prior density in Bayesian linear regression could accommodate such prior knowledge, formal models for doing so are absent from the literature. The goal of this article is therefore to develop a Bayesian model in which a linear regression analysis on current data is augmented with the reported regression coefficients (and standard errors) of previous studies. Two versions of this model are presented. The first version incorporates previous studies through the prior density and is applicable when the current and all previous studies are exchangeable. The second version models all studies in a hierarchical structure and is applicable when studies are not exchangeable. Both versions of the model are assessed using simulation studies. Performance for each in estimating the regression coefficients is consistently superior to using current data alone and is close to that of an equivalent model that uses the data from previous studies rather than reported regression coefficients. Overall the results show that augmenting data with results from previous studies is viable and yields significant improvements in the parameter estimation. |
| Databáze: | OpenAIRE |
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