<![CDATA[Epidemiology - Statistical testing]]>
http://journals.lww.com/epidem/pages/collectiondetails.aspx?TopicalCollectionId=4
en-usSun, 24 Jul 2016 10:30:13 -0500Wolters Kluwer Health RSS Generatorhttp://images.journals.lww.com/epidem/XLargeThumb.00001648-201607000-00000.CV.jpeg<![CDATA[Epidemiology - Statistical testing]]>
http://journals.lww.com/epidem/pages/collectiondetails.aspx?TopicalCollectionId=4
http://journals.lww.com/epidem/Fulltext/2001/05000/The_Value_of_P.2.aspx
<![CDATA[The Value of P]]>No abstract available]]>Thu, 01 Apr 2010 12:06:50 GMT-05:0000001648-200105000-00002
http://journals.lww.com/epidem/Fulltext/2001/05000/It_s_Time_to_Rehabilitate_the_P_Value.4.aspx
<![CDATA[It’s Time to Rehabilitate the P-Value]]>No abstract available]]>Thu, 01 Apr 2010 12:07:36 GMT-05:0000001648-200105000-00004
http://journals.lww.com/epidem/Fulltext/2001/05000/Low_P_Values_or_Narrow_Confidence_Intervals__Which.5.aspx
<![CDATA[Low P-Values or Narrow Confidence Intervals: Which Are More Durable?]]>No abstract available]]>Thu, 01 Apr 2010 12:08:13 GMT-05:0000001648-200105000-00005
http://journals.lww.com/epidem/Fulltext/2001/05000/Of_P_Values_and_Bayes__A_Modest_Proposal.6.aspx
<![CDATA[Of P-Values and Bayes: A Modest Proposal]]>No abstract available]]>Thu, 01 Apr 2010 12:08:58 GMT-05:0000001648-200105000-00006
http://pdfs.journals.lww.com/epidem/1998/01000/That_Confounded_P_Value_.4.pdf
<![CDATA[That Confounded P-Value.]]>No abstract available]]>Fri, 02 Jul 2010 15:12:25 GMT-05:0000001648-199801000-00004
http://pdfs.journals.lww.com/epidem/1990/01000/No_Adjustments_Are_Needed_for_Multiple.10.pdf
<![CDATA[No Adjustments Are Needed for Multiple Comparisons.]]>Adjustments for making multiple comparisons in large bodies of data are recommended to avoid rejecting the null hypothesis too readily. Unfortunately, reducing the type I error for null associations increases the type II error for those associations that are not null. The theoretical basis for advocating a routine adjustment for multiple comparisons is the "universal null hypothesis" that "chance" serves as the first-order explanation for observed phenomena. This hypothesis undermines the basic premises of empirical research, which holds that nature hollows regular laws that may he studied through observations. A policy of not making adjustments for multiple comparisons is preferable because it will lead to fewer errors of interpretation when the data under evaluation are not random numbers but actual observations on nature. Furthermore, scientists should not he so reluctant to explore leads that may turn out to he wrong that they penalize themselves by missing possibly important findings.
(C) Lippincott-Raven Publishers.]]>Fri, 02 Jul 2010 15:13:54 GMT-05:0000001648-199001000-00010
http://pdfs.journals.lww.com/epidem/1990/11000/Statistics_in_Nonrandomized_Studies_.1.pdf
<![CDATA[Statistics in Nonrandomized Studies.]]>No abstract available]]>Fri, 02 Jul 2010 15:14:53 GMT-05:0000001648-199011000-00001
http://pdfs.journals.lww.com/epidem/1993/11000/Causal_Inference_.13.pdf
<![CDATA[Causal Inference.]]>No abstract available]]>Fri, 02 Jul 2010 15:15:50 GMT-05:0000001648-199311000-00013
http://pdfs.journals.lww.com/epidem/1994/03000/ERRATUM_.27.pdf
<![CDATA[ERRATUM.]]>No abstract available]]>Fri, 02 Jul 2010 15:18:51 GMT-05:0000001648-199403000-00027
http://pdfs.journals.lww.com/epidem/1990/01000/Use_of_the_Confidence_Interval_function_.9.pdf
<![CDATA[Use of the Confidence Interval function.]]>Graphics displaying all confidence intervals around a point estimate have been referred to as P-value functions and consonance intervals. We recommend use of the term confidence interval function (CI function) rather than P-value function. The CI function is useful because it simultaneously depicts point estimation, variability, and the relation of these two factors to the null value. The usefulness of the CI function in demonstrating the concepts of effect modification and confounding, in meta-analysis, and in the comparison of various confidence interval procedures is evaluated. Software packages that produce CI functions are described.
(C) Lippincott-Raven Publishers.]]>Wed, 18 May 2011 14:30:03 GMT-05:0000001648-199001000-00009
http://pdfs.journals.lww.com/epidem/1991/07000/Empirical_Bayes_Adjustments_for_Multiple.2.pdf
<![CDATA[Empirical-Bayes Adjustments for Multiple Comparisons Are Sometimes Useful.]]>Rothman (Epidemiology 1990; 1:43-46) recommends against adjustments for multiple comparisons. Implicit in his recommendation, however, is an assumption that the sole objective of the data analysis is to report and scientifically interpret the data. We concur with his recommendation when this assumption is correct and one is willing to abandon frequentist interpretations of the summary statistics. Nevertheless, there are situations in which an additional or even primary goal of analysis is to reach a set of decisions based on the data. In such situations, Bayes and empirical-Bayes adjustments can provide a better basis for the decisions than conventional procedures
(C) Lippincott-Raven Publishers.]]>Tue, 14 Jun 2011 15:11:56 GMT-05:0000001648-199107000-00002
http://pdfs.journals.lww.com/epidem/1992/09000/Confidence_Limit_Analyses_Should_Replace_Power.11.pdf
<![CDATA[Confidence Limit Analyses Should Replace Power Calculations in the Interpretation of Epidemiologic Studies.]]>Frequently, after an epidemiologic study is completed, statistical power to detect a relative risk of interest is recalculated using data obtained during the course of the study. A negative study may then be dismissed on the grounds that its power was too low. However, post hoc power calculations ignore the actual relative estimate and its variance, which are by then known. We present evidence that post-study power calculations have little value and should be replaced by a more informative method using the upper (1 - [alpha]) % confidence limit of the point estimate that touches the value of the relative risk of interest. (Epidemiology 1992;3:449-452)
(C) Lippincott-Raven Publishers.]]>Tue, 14 Jun 2011 15:13:05 GMT-05:0000001648-199209000-00011
http://pdfs.journals.lww.com/epidem/1992/09000/Confidence_Interval_Estimation_of_Interaction_.12.pdf
<![CDATA[Confidence Interval Estimation of Interaction.]]>Relative excess risk due to interaction, the proportion of disease among those with both exposures that is attributable to their interaction, and the synergy index have been proposed as measures of interaction in epidemiologic studies. This paper presents the methodology for obtaining confidence interval estimates of these indices utilizing routinely available output from multiple logistic regression software. (Epidemiology 1992;3:452-456)
(C) Lippincott-Raven Publishers.]]>Tue, 14 Jun 2011 15:13:38 GMT-05:0000001648-199209000-00012
http://pdfs.journals.lww.com/epidem/1994/03000/Confidence_Limits_vs_Power_Calculations_.24.pdf
<![CDATA[Confidence Limits vs Power Calculations.]]>No abstract available]]>Tue, 14 Jun 2011 15:14:28 GMT-05:0000001648-199403000-00024
http://pdfs.journals.lww.com/epidem/1995/11000/Disease_Models_Implicit_in_Statistical_Tests_of.4.pdf
<![CDATA[Disease Models Implicit in Statistical Tests of Disease Clustering.]]>State and local health departments investigate an increasing number of cluster allegations, for which the selection of appropriate statistical methods is an important problem. Many of the methods for the spatial analysis of health data assume, either implicitly or explicitly, some model of disease occurrence, and comparisons of methods can be difficult when their underlying disease models differ. We review some of the issues involved in the statistical analysis of spatial disease patterns and describe several methods recently proposed to detect areas of increased disease rates. The disease models upon which the methods are based are explicitly described, and they provide a useful basis for comparing alternative clustering methods.
(C) Lippincott-Raven Publishers.]]>Tue, 14 Jun 2011 15:15:06 GMT-05:0000001648-199511000-00004
http://pdfs.journals.lww.com/epidem/1999/05000/The_P_Value_and_P_Value_Function_.27.pdf
<![CDATA[The P-Value and P-Value Function.]]>No abstract available]]>Tue, 14 Jun 2011 15:16:01 GMT-05:0000001648-199905000-00027
http://pdfs.journals.lww.com/epidem/1999/05000/The_Authors_Reply_.28.pdf
<![CDATA[The Authors Reply.]]>No abstract available]]>Tue, 14 Jun 2011 15:16:33 GMT-05:0000001648-199905000-00028
http://journals.lww.com/epidem/Fulltext/2013/01000/Living_with_P_Values__Resurrecting_a_Bayesian.9.aspx
<![CDATA[Living with P Values: Resurrecting a Bayesian Perspective on Frequentist Statistics]]>In response to the widespread abuse and misinterpretation of significance tests of null hypotheses, some editors and authors have strongly discouraged P values. However, null P values still thrive in most journals and are routinely misinterpreted as probabilities of a “chance finding” or of the null, when they are no such thing. This misuse may be lessened by recognizing correct Bayesian interpretations. For example, under weak priors, 95% confidence intervals approximate 95% posterior probability intervals, one-sided P values approximate directional posterior probabilities, and point estimates approximate posterior medians. Furthermore, under certain conditions, a one-sided P value for a prior median provides an approximate lower bound on the posterior probability that the point estimate is on the wrong side of that median. More generally, P values can be incorporated into a modern analysis framework that emphasizes measurement of fit, distance, and posterior probability in place of “statistical significance” and accept/reject decisions.]]>Tue, 18 Dec 2012 13:54:11 GMT-06:0000001648-201301000-00009
http://journals.lww.com/epidem/Fulltext/2013/01000/Rejoinder___Living_with_Statistics_in.11.aspx
<![CDATA[Rejoinder: Living with Statistics in Observational Research]]>No abstract available]]>Tue, 18 Dec 2012 13:54:34 GMT-06:0000001648-201301000-00011
http://journals.lww.com/epidem/Fulltext/2013/01000/Rejoinder___Living_with_Statistics_in.11.aspx
<![CDATA[Rejoinder: Living with Statistics in Observational Research]]>No abstract available]]>Tue, 18 Dec 2012 13:54:56 GMT-06:0000001648-201301000-00011
http://journals.lww.com/epidem/Fulltext/2013/03000/Commentary___Reconciling_Theory_and_Practice__What.7.aspx
<![CDATA[Commentary: Reconciling Theory and Practice: What Is to Be Done with P Values?]]>No abstract available]]>Fri, 22 Feb 2013 16:38:44 GMT-06:0000001648-201303000-00007