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Multiple-test procedures and smile plots

Author

Listed:
  • Roger Newson

    () (King's College London)

  • The ALSPAC Study Team

    (University of Bristol)

Abstract

multproc carries out multiple-test procedures, taking as input a list of p-values and an uncorrected critical p-value, and calculating a corrected overall critical pvalue for rejection of null hypotheses. These procedures define a conÞdence region for a set-valued parameter, namely the set of null hypotheses that are true. They aim to control either the family-wise error rate (FWER) or the false discovery rate (FDR) at a level no greater than the uncorrected critical p-value. smileplot calls multproc and then creates a smile plot, with data points corresponding to estimated parameters, the p-values (on a reverse log scale) on the y-axis, and the parameter estimates (or another variable) on the x-axis. There are y-axis reference lines at the uncorrected and corrected overall critical p-values. The reference line for the corrected overall critical p-value, known as the parapet line, is an informal Òupper confidence limitÓ for the set of null hypotheses that are true and defines a boundary between data mining and data dredging. A smile plot summarizes a set of multiple analyses just as a Cochrane forest plot summarizes a meta-analysis. Copyright 2003 by Stata Corporation.

Suggested Citation

  • Roger Newson & The ALSPAC Study Team, 2003. "Multiple-test procedures and smile plots," Stata Journal, StataCorp LP, vol. 3(2), pages 109-132, June.
  • Handle: RePEc:tsj:stataj:v:3:y:2003:i:2:p:109-132
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    References listed on IDEAS

    as
    1. Roger Newson, 2000. "A program for saving a model fit as a dataset," Stata Technical Bulletin, StataCorp LP, vol. 9(49).
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    Cited by:

    1. repec:ucp:jlabec:doi:10.1086/690652 is not listed on IDEAS
    2. Böhme, Marcus H. & Persian, Ruth & Stöhr, Tobias, 2015. "Alone but better off? Adult child migration and health of elderly parents in Moldova," Journal of Health Economics, Elsevier, vol. 39(C), pages 211-227.
    3. Bell, Suzanne & Prata, Ndola & Lahiff, Maureen & Eskenazi, Brenda, 2012. "Civil unrest and birthweight: An exploratory analysis of the 2007/2008 Kenyan Crisis," Social Science & Medicine, Elsevier, vol. 74(9), pages 1324-1330.
    4. Roger M. Harbord & Julian P.T. Higgins, 2008. "Meta-regression in Stata," Stata Journal, StataCorp LP, vol. 8(4), pages 493-519, December.
    5. Gisselquist, Rachel M. & Leiderer, Stefan & Niño-Zarazúa, Miguel, 2016. "Ethnic Heterogeneity and Public Goods Provision in Zambia: Evidence of a Subnational “Diversity Dividend”," World Development, Elsevier, vol. 78(C), pages 308-323.
    6. Günther Fink & Margaret McConnell & Sebastian Vollmer, 2014. "Testing for heterogeneous treatment effects in experimental data: false discovery risks and correction procedures," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 6(1), pages 44-57, January.
    7. Dunsch, Felipe A. & Evans, David K. & Eze-Ajoku, Ezinne & Macis, Mario, 2017. "Management, Supervision, and Health Care: A Field Experiment," IZA Discussion Papers 10967, Institute for the Study of Labor (IZA).
    8. Michael J. Kottelenberg & Steven F. Lehrer, 2017. "Targeted or Universal Coverage? Assessing Heterogeneity in the Effects of Universal Child Care," Journal of Labor Economics, University of Chicago Press, vol. 35(3), pages 609-653.
    9. Roger B. Newson, 2010. "Frequentist q-values for multiple-test procedures," Stata Journal, StataCorp LP, vol. 10(4), pages 568-584, December.
    10. repec:eee:joepsy:v:64:y:2018:i:c:p:18-48 is not listed on IDEAS
    11. Roger Newson, 2008. "parmest and extensions," United Kingdom Stata Users' Group Meetings 2008 07, Stata Users Group.
    12. Roger B. Newson, 2013. "Bonferroni and Holm approximations for Sidak and Holland–Copenhaver q-values," Stata Journal, StataCorp LP, vol. 13(2), pages 379-381, June.

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