BMC Medical Research Methodology - Latest Comments
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The latest comments on all articles published by BMC Medical Research Methodology2014-07-28T09:50:12ZIssues regarding simulation study and conclusions
http://www.biomedcentral.com/1471-2288/14/49/comments#2134698
The topic of covariate adjustment in randomised trials is an important one. However, I believe the simulation study and conclusions of Edgewale are flawed, and moreover my concerns mirror those of one of the paper's original reviewer's (Gillian Raab), which appear not to have been dealt with.<br /><br />The authors investigate the performance of three methods for analysing randomised trials with a single continuous outcome and a corresponding baseline measure. They focus on the issue of baseline imbalance, and conduct a simulation study where trial data are generated such that there is, on average, an imbalance at baseline between the two treatment groups. From their simulation results, the authors conclude that ANCOVA is unbiased, whereas analysis of change scores and an unadjusted comparison of outcomes (ignoring baseline) are biased.<br /><br />The problem is that the above approach for generating data does not correspond to how data arise in randomised trials. As the authors explain in the introduction, randomisation guarantees balance in expectation or on average, but not balance in any given study. But in the simulation study conducted, data are generated so that there is systematically (i.e. on average) imbalance at baseline. It is therefore unsurprising that in this case the ANOVA analysis (a t-test of outcomes ignoring baseline) is biased. All this demonstrates is that if one has a confounder, and one does not adjust for the confounder, estimates are biased. Put another way, the simulations show the following: if one performs repeated randomised trials where patients are more likely to be allocated to one of the treatment groups if they have higher baseline values, then a ANOVA or analysis of change scores is biased. But of course this is not how patients are allocated to groups in a simple randomised trial!<br /><br />In a randomised trial, provided that the randomisation procedure is not compromised, all three of the methods considered by the authors are unbiased, at least according to the statistical definition of bias of an estimator as the difference between the expectation of the estimator and the true parameter value. The methods do however differ in terms of precision/efficiency, and previously it has been shown that ANCOVA is superior in this regard to the other two methods. All of these results can be found in the following paper:<br /><br />Yang L, Tsiatis A (2001). Efficiency study of estimators for a treatment effect in a pretest-posttest trial. The American Statistician; 55: 314-321.Jonathan Bartlett2014-07-28T09:50:12Zhttp://www.biomedcentral.com/1471-2288/14/49Egbewale et al.BMC Medical Research Methodology1449Wed Apr 09 00:00:00 BST 2014Correction to funding acknowledgement for this paper
http://www.biomedcentral.com/1471-2288/14/21/comments#2123698
<p>This study was funded through the East Africa International epidemiological Databases to Evaluate AIDS (IeDEA) Consortium by the US National Institutes of Health - the Eunice Kennedy Shriver National Institute Of Child Health & Human Development (NICHD) and the National Institute Of Allergy And Infectious Diseases (NIAID). Grant award 3U01AI069911-06S2.</p>
<p> </p>Annabelle Gourlay2014-06-25T13:30:51Zhttp://www.biomedcentral.com/1471-2288/14/21Gourlay et al.BMC Medical Research Methodology1421Tue Feb 11 00:00:00 GMT 2014Software
http://www.biomedcentral.com/1471-2288/13/35/comments#2030698
The functions for assessing the heterogeneity and inconsistency in network meta-analysis, for producing a net heat plot and a network graph are now implemented in the R package netmeta with version 0.4-0 and are available from the standard <a class="external-link-new-window" href="http://www.cran.r-project.org/">CRAN repository</a>.Ulrike Krahn2014-03-28T16:31:24Zhttp://www.biomedcentral.com/1471-2288/13/35Krahn et al.BMC Medical Research Methodology1335Sat Mar 09 00:00:00 GMT 2013Ridge parameter
http://www.biomedcentral.com/1471-2288/12/184/comments#1279696
<p>The paper by Hardt, Herke and Leonhart is a welcome addition to the literature. It warns against simplistic approaches that throw just anything into the imputation model. While the imputation model is generally robust against including junk variables, the paper clearly demonstrates that we should not drive this to the edge. In general building the imputation model requires appropriate care. My personal experience is that it is not beneficial to include more than -say- 25 well-chosen variables into the imputation model.
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<br/>In their simulations the authors investigate cases where the number of variables specified in the imputation model exceeds the number of cases. Many programs break down in this case, but MICE will run because it uses ridge regression instead of the usual OLS estimate. The price for this increased computational stability is -as confirmed by Hardt et all - that the parameters estimates will be biased towards zero. It is therefore likely that some of the bias observed by the authors is not intrinsic to PMM, but rather due to the setting of the ridge parameter (the default value 1E-5 may be easily changed as mice(..., ridge = 1E-6)). Would a tighter ridge setting (e.g., 1E-6 or 1E-7) appreciably reduce the bias?
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<br/>The '1 out of 3 of the complete cases' rule is interesting and easily remembered. However, a complication in practice is that there are often no complete cases in real data, especially in merged datasets. What would the authors think of the slightly more liberal rule 'n/3 variables'?
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<br/>Stef van Buuren</p>Stef van Buuren2013-02-15T14:56:37Zhttp://www.biomedcentral.com/1471-2288/12/184Hardt et al.BMC Medical Research Methodology12184Wed Dec 05 00:00:00 GMT 2012erratum
http://www.biomedcentral.com/1471-2288/7/36/comments#1042696
<p>This commentary serves to point out that in the results section (p.7) of the manuscript, we (the authors) incorrectly described the calculation of specificity of VIA for the 3-class model. The corrected text (below) describes a specificity of 0.65 versus 0.57. The calculation correction is also appended.
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<br/>"Specificity was 0.645. In that model, class 1 (p = 0.682) and class 2 (p = 0.200) combine to form non-disease. Specificity was calculated as 0.323 (probability of VIA inflammation given class 2) plus 0.117 (probability of VIA normal given class 2) multiplied by the probability of class 2 (0.200), plus the analogous values for Class 1, i.e., 0.429 (probability of VIA inflammation given class 1) plus 0.276 (probability of VIA normal given class 1) multiplied by the probability of class 1 (0.682), the entire sum being divided by the probability of non-disease (0.682 + 0.200)."
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<br/>In Table 4, the specificity values for the 3-class LCA solution reference standard (#4) are likewise incorrect. These values were given as 0.568, 0.820, 0.568, 0.758, and 0.860 for, respectively, VIA Abnormal, CA; Pap LGSIL+; HPV >= 1.0 RLU; Colposcopy/Biopsy LGSIL+; and Colposcopy/Biopsy HGSIL+. The correct values are all higher and should be listed as 0.645, 0.930, 0.644, 0.860, and 0.975.
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<br/>In keeping with the above, the following text (pages 6-7) should be corrected as follows (0.645 instead of 0.568):
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<br/>"In this study, despite apparent imperfections in the reference standard, the conventionally-derived VIA results fell within the range of published data and were relatively consistent between with the 3-class LCA model (0.775 versus 0.744, respectively, for sensitivity and 0.639 and 0.645, respectively for specificity)."
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<br/>These corrections do not substantively alter the results (as noted above, the corrected LCA-derived specificity value is now almost the same as the conventionally derived value, similar to what was observed for VIA for sensitivity) and the corrections do not affect our conclusions.</p>John McGrath2012-08-02T14:47:45Zhttp://www.biomedcentral.com/1471-2288/7/36Gaffikin et al.BMC Medical Research Methodology736Tue Jul 31 01:34:30 BST 2007Correction
http://www.biomedcentral.com/1471-2288/11/96/comments#1027698
<p>Equation 12 contains errors. In the equation k_min should be replaced by k_1, k_max with k_K and k_K-j with k_K-j+1. Below equation 12, in the description of lambda_j, k_K-j should again be replaced with k_K-j+1. We would like to thank Dr. Finian Bannon at the N. Ireland Cancer Registry for pointing out these errors.</p>Therese Andersson2012-08-02T12:15:04Zhttp://www.biomedcentral.com/1471-2288/11/96Andersson et al.BMC Medical Research Methodology1196Wed Jun 22 00:00:00 BST 2011Update on methodology for NSW Ministy of Health telephone surveys
http://www.biomedcentral.com/1471-2288/11/159/comments#924696
<p>As referenced in the article landline random digit dialling (RDD) have been the method of choice for the telephone based population health survey conducted by the NSW Ministry of Health over the last decade. However because of the increase in mobile phone ownership the methology was modified to include mobile only persons using an overlapping duel-frame design in 2012. The methodology was developed in collaboration with the Centre for Statistical and Survey Methodology at the University of Wollongong. A full description of the methods and preliminary findings will be available soon.</p>Margo Barr2012-06-24T14:38:47Zhttp://www.biomedcentral.com/1471-2288/11/159Liu et al.BMC Medical Research Methodology11159Thu Nov 24 00:00:00 GMT 2011Quantum Biophysical Semeiotics plays a central role in predicting intracranial findings on CT-scans.
http://www.biomedcentral.com/1471-2288/11/143/comments#628695
<p>Editors, <br/>in order to recognize, among individuals involved by suspected traumatic brain damage, those who really is suffering from such a disorder, physicians nowadays can utilise Quantum Biophysical Semeiotics (1-4). <br/>For instance, in health, light digital pressure, applied upon the closed eye, brings about gastric aspecific reflex (= both stomach fundus and body dilates) after a latency time of 8 sec. <br/>On the contrary, in presence of a pathological condition latency time results smaller, in relation to the seriousness of underlying disorder. <br/>An awful number of other signs allow doctor to make a correct differential diagnosis. <br/> <br/> <br/>References <br/> <br/> <br/>1) Stagnaro S., Percussione Ascoltata degli Attacchi Ischemici Transitori. Ruolo dei Potenziali Cerebrali Evocati. Min. Med. 76, 1211 [Pub-Med indicizzato per Medline] <br/>2) Stagnaro Sergio, Stagnaro-Neri Marina. Introduzione alla Semeiotica Biofisica. Il Terreno oncologico”. Travel Factory SRL., Roma, 2004. http://www.travelfactory.it/semeiotica_biofisica.htm <br/>3) Stagnaro S., Stagnaro-Neri M., Single Patient Based Medicine.La Medicina Basata sul Singolo Paziente: Nuove Indicazioni della Melatonina. Travel Factory SRL., Roma, 2005. http://www.travelfactory.it/semeiotica_biofisica.htm <br/>4) Stagnaro Sergio. Inherited Real Risk of Brain Disorders. www.plos.org, 24 July 2009. http://www.plosone.org/article/comments/info%3Adoi%2F10.1371%2Fjournal.pone.0006354;jsessionid=9AC82C42FA9F57C913844806BF96DDC1 <br/></p>Sergio Stagnaro2011-12-02T17:25:34Zhttp://www.biomedcentral.com/1471-2288/11/143van der Ploeg et al.BMC Medical Research Methodology11143Tue Oct 25 00:00:00 BST 2011Further early references to sample sizes with fixed number of clusters
http://www.biomedcentral.com/1471-2288/11/102/comments#570694
<p>Hemming et al (2011) give a useful review of sample size calculations with a fixed number of clusters. As they acknowledge their equations (17) to (19) are derived from Donner and Klar (200). I would like to point out the issue of fixed number of clusters was also discussed by Campbell (2000) that the authors’ equation (13) was first given as equation (2) in that paper and as equation (9.7) in Machin and Campbell (2005). <br/> <br/>Mike Campbell <br/> <br/>References <br/>Campbell MJ Cluster randomized trials in general (family) practice research. Statistical Methods in Medical Research 2000, 9; 81-94 <br/> <br/>Donner A and Klar N. Design and analysis of cluster randomized trials. London, Arnold 2000 <br/> <br/>Machin D and Campbell MJ Design of Studies for Medical Research. Chichester, John Wiley and Sons Ltd, 2005 <br/></p>Michael Campbell2011-09-12T16:34:29Zhttp://www.biomedcentral.com/1471-2288/11/102Hemming et al.BMC Medical Research Methodology11102Thu Jun 30 00:00:00 BST 2011Two errors in this article?
http://www.biomedcentral.com/1471-2288/11/23/comments#535685
<p>I can't find a definition for FORM in the article. it appears for the first time in the Method section on page 3 but does not have a definition. Is there one? <br/> <br/>Also, there appears to be an error in Table 1, in the cell combining "Consistency" and "D Poor". It says 'Evidence is consistent' however it should read 'Evidence is inconsistent'. </p>Emma Friesen2011-07-04T10:54:28Zhttp://www.biomedcentral.com/1471-2288/11/23Hillier et al.BMC Medical Research Methodology1123Mon Feb 28 09:14:39 GMT 2011