Holly Janes

Summary

Affiliation: University of Washington
Country: USA

Publications

  1. ncbi request reprint Identifying target populations for screening or not screening using logic regression
    Holly Janes
    Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
    Stat Med 24:1321-38. 2005
  2. pmc Net risk reclassification p values: valid or misleading?
    Margaret S Pepe
    Affiliations of authors Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA MSP, HJ, CIL Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA HJ
    J Natl Cancer Inst 106:dju041. 2014
  3. doi request reprint Statistical analysis of air pollution panel studies: an illustration
    Holly Janes
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, University of Washington, Seattle, USA
    Ann Epidemiol 18:792-802. 2008
  4. pmc On quantifying the magnitude of confounding
    Holly Janes
    Vaccine and Infectious Disease Institute and Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North M2 C200, Seattle, WA 98109, USA
    Biostatistics 11:572-82. 2010
  5. doi request reprint Fine particulate matter and mortality: a comparison of the six cities and American Cancer Society cohorts with a medicare cohort
    Sorina E Eftim
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Epidemiology 19:209-16. 2008
  6. ncbi request reprint Case-crossover analyses of air pollution exposure data: referent selection strategies and their implications for bias
    Holly Janes
    Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
    Epidemiology 16:717-26. 2005
  7. ncbi request reprint The optimal ratio of cases to controls for estimating the classification accuracy of a biomarker
    Holly Janes
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205, USA
    Biostatistics 7:456-68. 2006
  8. pmc Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design
    Margaret S Pepe
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 1024, USA
    J Natl Cancer Inst 100:1432-8. 2008
  9. ncbi request reprint Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker
    Margaret Sullivan Pepe
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
    Am J Epidemiol 159:882-90. 2004
  10. ncbi request reprint Matching in studies of classification accuracy: implications for analysis, efficiency, and assessment of incremental value
    Holly Janes
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, USA
    Biometrics 64:1-9. 2008

Detail Information

Publications21

  1. ncbi request reprint Identifying target populations for screening or not screening using logic regression
    Holly Janes
    Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
    Stat Med 24:1321-38. 2005
    ..However, we believe that our novel statistical approach could be useful in settings where risk factors do discriminate between cases and controls, and illustrate this with a simulated data set...
  2. pmc Net risk reclassification p values: valid or misleading?
    Margaret S Pepe
    Affiliations of authors Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA MSP, HJ, CIL Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA HJ
    J Natl Cancer Inst 106:dju041. 2014
    ..Although proposed only 5 years ago, the NRI has gained enormous traction in the risk prediction literature. Concerns have recently been raised about the statistical validity of the NRI...
  3. doi request reprint Statistical analysis of air pollution panel studies: an illustration
    Holly Janes
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, University of Washington, Seattle, USA
    Ann Epidemiol 18:792-802. 2008
    ..Standard statistical methods are available for analyzing longitudinal data, but the literature reveals that these methods are poorly understood by practitioners...
  4. pmc On quantifying the magnitude of confounding
    Holly Janes
    Vaccine and Infectious Disease Institute and Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North M2 C200, Seattle, WA 98109, USA
    Biostatistics 11:572-82. 2010
    ..In settings with a sizable nonlinearity effect, the corrected estimate of confounding has improved performance...
  5. doi request reprint Fine particulate matter and mortality: a comparison of the six cities and American Cancer Society cohorts with a medicare cohort
    Sorina E Eftim
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Epidemiology 19:209-16. 2008
    ..5) on mortality. Using Medicare data, we assessed the association of PM2.5 with mortality for the same locations included in these studies...
  6. ncbi request reprint Case-crossover analyses of air pollution exposure data: referent selection strategies and their implications for bias
    Holly Janes
    Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
    Epidemiology 16:717-26. 2005
    ....
  7. ncbi request reprint The optimal ratio of cases to controls for estimating the classification accuracy of a biomarker
    Holly Janes
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205, USA
    Biostatistics 7:456-68. 2006
    ..Our methods are applied to a study of a new marker for adenocarcinoma in patients with Barrett's esophagus...
  8. pmc Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design
    Margaret S Pepe
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 1024, USA
    J Natl Cancer Inst 100:1432-8. 2008
    ..Common biases that pervade the biomarker research literature would be eliminated if these rigorous standards were followed...
  9. ncbi request reprint Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker
    Margaret Sullivan Pepe
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
    Am J Epidemiol 159:882-90. 2004
    ..In addition, the serious pitfalls of using more traditional methods based on parameters in logistic regression models are illustrated...
  10. ncbi request reprint Matching in studies of classification accuracy: implications for analysis, efficiency, and assessment of incremental value
    Holly Janes
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, USA
    Biometrics 64:1-9. 2008
    ..However, we also show that matching greatly complicates estimation of the incremental value of the marker. We recommend that matching be carefully considered in the context of these findings...
  11. pmc New clinical trial designs for HIV vaccine evaluation
    Zoe Moodie
    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, University of Washington, Seattle, WA 98109, USA
    Curr Opin HIV AIDS 8:437-42. 2013
    ....
  12. ncbi request reprint Adjusting for covariates in studies of diagnostic, screening, or prognostic markers: an old concept in a new setting
    Holly Janes
    Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
    Am J Epidemiol 168:89-97. 2008
    ..They draw analogies and contrasts throughout with studies of association...
  13. pmc Measuring the performance of markers for guiding treatment decisions
    Holly Janes
    Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
    Ann Intern Med 154:253-9. 2011
    ..Randomized therapeutic clinical trials, in which entry criteria and treatment regimens are not restricted by the marker, are also proposed as the basis for constructing the curves and evaluating and comparing markers...
  14. pmc Assessing treatment-selection markers using a potential outcomes framework
    Ying Huang
    Fred Hutchinson Cancer Research Center, Seattle, Washington, 98109, USA
    Biometrics 68:687-96. 2012
    ..Finally, we illustrate the methods using an HIV vaccine trial where we explore the value of the level of preexisting immunity to adenovirus serotype 5 for predicting a vaccine-induced increase in the risk of HIV acquisition...
  15. pmc Assessing the value of risk predictions by using risk stratification tables
    Holly Janes
    Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
    Ann Intern Med 149:751-60. 2008
    ....
  16. ncbi request reprint Trends in air pollution and mortality: an approach to the assessment of unmeasured confounding
    Holly Janes
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
    Epidemiology 18:416-23. 2007
    ..5 and mortality at the local scale. If the association at the national scale is set aside, there is little evidence of an association between 12-month exposure to PM2.5 and mortality...
  17. ncbi request reprint Overlap bias in the case-crossover design, with application to air pollution exposures
    Holly Janes
    Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
    Stat Med 24:285-300. 2005
    ..We give a derivation of overlap bias, explore its magnitude, and consider how the bias depends on properties of the exposure series. We conclude that the bias is usually small, though highly unpredictable, and easily avoided...
  18. pmc Net reclassification indices for evaluating risk prediction instruments: a critical review
    Kathleen F Kerr
    From the aDepartment of Biostatistics, University of Washington, Seattle, WA bFred Hutchinson Cancer Research Center, University of Washington, Seattle, WA and cCardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Group Health Research Institute, Group Health Cooperative, Seattle, WA
    Epidemiology 25:114-21. 2014
    ..The preferred single-number summary of the prediction increment is the improvement in net benefit. ..
  19. ncbi request reprint Insights into latent class analysis of diagnostic test performance
    Margaret Sullivan Pepe
    Department of Biostatistics, University of Washington and Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
    Biostatistics 8:474-84. 2007
    ..Such justification must be based in part on a clear clinical definition of disease and biological knowledge about mechanisms giving rise to test results...
  20. ncbi request reprint Letter by Pepe et al regarding article, "Use and misuse of the receiver operating characteristic curve in risk prediction"
    Margaret S Pepe
    Circulation 116:e132; author reply e134. 2007
  21. ncbi request reprint Do subject characteristics modify the effects of particulate air pollution on daily mortality among the elderly?
    Holly Janes
    J Occup Environ Med 47:543; author reply 543-5. 2005