Combining data from 2 nested case-control studies of overlapping cohorts to improve efficiency
Researchers subject to time and budget constraints may conduct small nested case-control studies with individually matched controls to help optimize statistical power. In this paper, we show how precision can be improved considerably by combining data from a small nested case-control study with data...
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Published in | Biostatistics (Oxford, England) Vol. 10; no. 1; pp. 70 - 79 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
England
Oxford University Press
01.01.2009
Oxford Publishing Limited (England) |
Subjects | |
Online Access | Get full text |
ISSN | 1465-4644 1468-4357 1468-4357 |
DOI | 10.1093/biostatistics/kxn016 |
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Abstract | Researchers subject to time and budget constraints may conduct small nested case-control studies with individually matched controls to help optimize statistical power. In this paper, we show how precision can be improved considerably by combining data from a small nested case-control study with data from a larger nested case-control study of a different outcome in the same or overlapping cohort. Our approach is based on the inverse probability weighting concept, in which the log-likelihood contribution of each individual observation is weighted by the inverse of its probability of inclusion in either study. We illustrate our approach using simulated data and an application where we combine data sets from 2 nested case-control studies to investigate risk factors for anorexia nervosa in a cohort of young women in Sweden. |
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AbstractList | Researchers subject to time and budget constraints may conduct small nested case-control studies with individually matched controls to help optimize statistical power. In this paper, we show how precision can be improved considerably by combining data from a small nested case-control study with data from a larger nested case-control study of a different outcome in the same or overlapping cohort. Our approach is based on the inverse probability weighting concept, in which the log-likelihood contribution of each individual observation is weighted by the inverse of its probability of inclusion in either study. We illustrate our approach using simulated data and an application where we combine data sets from 2 nested case-control studies to investigate risk factors for anorexia nervosa in a cohort of young women in Sweden. Researchers subject to time and budget constraints may conduct small nested case-control studies with individually matched controls to help optimize statistical power. In this paper, we show how precision can be improved considerably by combining data from a small nested case-control study with data from a larger nested case-control study of a different outcome in the same or overlapping cohort. Our approach is based on the inverse probability weighting concept, in which the log-likelihood contribution of each individual observation is weighted by the inverse of its probability of inclusion in either study. We illustrate our approach using simulated data and an application where we combine data sets from 2 nested case-control studies to investigate risk factors for anorexia nervosa in a cohort of young women in Sweden.Researchers subject to time and budget constraints may conduct small nested case-control studies with individually matched controls to help optimize statistical power. In this paper, we show how precision can be improved considerably by combining data from a small nested case-control study with data from a larger nested case-control study of a different outcome in the same or overlapping cohort. Our approach is based on the inverse probability weighting concept, in which the log-likelihood contribution of each individual observation is weighted by the inverse of its probability of inclusion in either study. We illustrate our approach using simulated data and an application where we combine data sets from 2 nested case-control studies to investigate risk factors for anorexia nervosa in a cohort of young women in Sweden. Researchers subject to time and budget constraints may conduct small nested case-control studies with individually matched controls to help optimize statistical power. In this paper, we show how precision can be improved considerably by combining data from a small nested case-control study with data from a larger nested case-control study of a different outcome in the same or overlapping cohort. Our approach is based on the inverse probability weighting concept, in which the log-likelihood contribution of each individual observation is weighted by the inverse of its probability of inclusion in either study. We illustrate our approach using simulated data and an application where we combine data sets from 2 nested case-control studies to investigate risk factors for anorexia nervosa in a cohort of young women in Sweden. [PUBLICATION ABSTRACT] |
Author | Salim, Agus Hultman, Christina Sparén, Pär Reilly, Marie |
Author_xml | – sequence: 1 givenname: Agus surname: Salim fullname: Salim, Agus email: cofaguss@nus.edu.sg – sequence: 2 givenname: Christina surname: Hultman fullname: Hultman, Christina email: cofaguss@nus.edu.sg – sequence: 3 givenname: Pär surname: Sparén fullname: Sparén, Pär email: cofaguss@nus.edu.sg – sequence: 4 givenname: Marie surname: Reilly fullname: Reilly, Marie email: cofaguss@nus.edu.sg |
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Cites_doi | 10.1136/bmj.318.7181.421 10.1002/sim.2398 10.1093/biomet/65.1.153 10.1001/archpsyc.56.7.634 10.2307/2986303 10.1093/biomet/84.2.379 10.2307/2345280 10.1093/biomet/65.1.141 10.1002/sim.2283 |
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References | Hultman (4_10725333) 1999; 318 (6_29710746) 1977; 140 Cnattingius (3_10883328) 1999; 56 CLAYTON (2_21359728) 1978; 65 PRENTICE (8_21359730) 1978; 65 SAMUELSEN (10_20299710) 1997; 84 Jiang (5_21872322) 2006; 25 (12_29714036) 1980; 29 Reilly (9_19716241) 2005; 24 |
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SubjectTerms | Anorexia Anorexia Nervosa - epidemiology Anorexia Nervosa - etiology Biomedical research Biometry - methods Case-Control Studies Cohort Studies Data Collection - methods Female Humans Likelihood Functions Meta-Analysis as Topic Optimization Probability Proportional Hazards Models Psychotic Disorders - epidemiology Psychotic Disorders - etiology Risk Factors Sample Size Schizophrenia - epidemiology Schizophrenia - etiology Statistical analysis Sweden |
Title | Combining data from 2 nested case-control studies of overlapping cohorts to improve efficiency |
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