On contemporaneous controls, unlikely outcomes, boxes and replacing the 'Student': good statistical practice in pharmacology, problem 3.
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ABSTRACT:
SUBMITTER: Lew MJ
PROVIDER: S-EPMC2597241 | biostudies-other | 2008 Nov
REPOSITORIES: biostudies-other
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Project description:BACKGROUND AND PURPOSE: This paper is intended to assist pharmacologists in making the most of statistical analysis and in avoiding common errors that can lead to false conclusions. APPROACH: A scenario is presented where a pathway inhibitor increased blood pressure responses to an agonist by about one third. The fictional experimenter concludes that the inhibitor enhanced the responses to the agonist, but has not applied any statistical analysis. Questions are asked of the reader, and a discussion of the author's answers is presented. RESULTS: The agonist responses have unequal standard errors, as often seen in data like these concentration-response curves with responses expressed as change from baseline. The uneven variability (heteroscedasticity) violates an assumption of conventional parametric statistical analyses, but can be corrected by data transformation. Expressing the data as absolute blood pressure and then transforming it to log blood pressure eliminated the heteroscedasticity, but made evident an effect of the inhibitor on baseline blood pressure. CONCLUSIONS AND IMPLICATIONS: Statistical analysis is a sensible precaution against mistakes, but cannot protect against all erroneous conclusions. In this scenario, the inhibitor reduced the blood pressure and increased responses to the agonist. However, it is likely that the latter effect was a consequence of the former and thus no conclusion can be safely drawn about any direct interaction between the agonist and the pathway inhibitor from this experiment. Where results are awkward to interpret because of confounding factors such as an altered baseline, statistical analysis may not be very useful in supporting a safe conclusion.
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Project description:BACKGROUND AND PURPOSE: This paper is intended to assist pharmacologists to make the most of statistical analysis and in avoid common errors. APPROACH: A scenario is presented where an experimenter performed an experiment to test the effects of two drugs on cultured cells. Analysis of the results, expressed as percentage of control, by a one-way ANOVA yielded P=0.058 and the experimenter concluded that neither drug was effective. The data were expressed as percentage of control because of pairing of the data within each experimental run, a common feature in cell culture experiments. Such data can be analysed with potentially more powerful ANOVA methods equivalent to the paired t-test. Monte Carlo simulations are presented to compare the power of relevant analyses. RESULTS: For data correlated within experimental run (i.e. paired values), transformation to percentage of control improved the power of a one-way ANOVA to detect a real effect, but a randomized block ANOVA (equivalent to a 2-way ANOVA with experiment and treatment as factors) using the raw values was substantially more powerful. The randomized block ANOVA performed well even with uncorrelated data, being only marginally less powerful than the one-way ANOVA. CONCLUSIONS AND IMPLICATIONS: A randomized block ANOVA is far superior to the one-way ANOVA with correlated data, and with uncorrelated data it is only marginally less powerful. Thus where there is, or might reasonably be, such a correlation (e.g. relatedness among the data within a single experimental run, or within a multi-well culture plate, or within an animal, et cetera), use the more powerful randomized block ANOVA rather than one-way ANOVA.
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Project description:PurposeTo examine the variability among medical schools in ranking systems used in medical student performance evaluations (MSPEs).MethodThe authors reviewed MSPEs from U.S. MD-granting medical schools received by the University of California, Irvine emergency medicine and internal medicine residency programs during 2012-2013 and 2014-2015. They recorded whether the school used a ranking system, the type of ranking system used, the size and description of student categories, the location of the ranking statement and category legend, and whether nonranking schools used language suggestive of rank.ResultsOf the 134 medical schools in the study sample, the majority (n = 101; 75%) provided ranks for students in the MSPE. Most of the ranking schools (n = 63; 62%) placed students into named category groups, but the number and size of groups varied. The most common descriptors used for these 63 schools' top, second, third, and lowest groups were "outstanding," "excellent," "very good," and "good," respectively, but each of these terms was used across a broad range of percentile ranks. Student ranks and school category legends were found in various locations. Many of the 33 schools that did not rank students included language suggestive of rank.ConclusionsThere is extensive variation in ranking systems used in MSPEs. Program directors may find it difficult to use MSPEs to compare applicants, which may diminish the MSPE's value in the residency application process and negatively affect high-achieving students. A consistent approach to ranking students would benefit program directors, students, and student affairs officers.
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Project description:Loot boxes are items in video games that can be paid for with real-world money but contain randomized contents. Many games that feature loot boxes are played by adolescents. Similarities between loot boxes and gambling have led to concern that they are linked to the development of problem gambling in adolescents. Previous research has shown links between loot boxes and problem gambling in adult populations. However, thus far, there is no empirical evidence of either the size or existence of a link between loot box spending and problem gambling in adolescents. A large-scale survey of 16- to 18-year-olds (n = 1155) found evidence for such a link (η 2 = 0.120). The link between loot box spending and problem gambling among these older adolescents was of moderate to large magnitude. It was stronger than relationships previously observed in adults. Qualitative analysis of text data showed that gamers bought loot boxes for a variety of reasons. Several of these motivations were similar to common reasons for engaging in gambling. Overall, these results suggest that loot boxes either cause problem gambling among older adolescents, allow game companies to profit from adolescents with gambling problems for massive monetary rewards, or both of the above. Possible strategies for regulation and restriction are given.
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Project description:AimsCollege students experience high rates of problem and pathological gambling, yet little research has investigated methods for reducing gambling in this population. This study sought to examine the efficacy of brief intervention strategies.DesignRandomized trial.SettingCollege campuses.ParticipantsA total of 117 college student problem and pathological gamblers.InterventionsStudents were assigned randomly to: an assessment-only control, 10 minutes of brief advice, one session of motivational enhancement therapy (MET) or one session of MET, plus three sessions of cognitive-behavioral therapy (CBT). The three interventions were designed to reduce gambling.MeasurementsGambling was assessed at baseline, week 6 and month 9 using the Addiction Severity Index-gambling (ASI-G) module, which also assesses days and dollars wagered.FindingsCompared to the assessment-only condition, those receiving any intervention had significant decreases in ASI-G scores and days and dollars wagered over time. The MET condition decreased significantly ASI-G scores and dollars wagered over time, and increased the odds of a clinically significant reduction in gambling at the 9-month follow-up relative to the assessment-only condition, even after controlling for baseline indices that could impact outcomes. The Brief Advice and MET+CBT conditions had benefits on some, but not all, indices of gambling. None of the interventions differed significantly from one another. Conclusions These results suggest the efficacy of brief interventions for reducing gambling problems in college students.
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Project description:The statistical matching problem involves the integration of multiple datasets where some variables are not observed jointly. This missing data pattern leaves most statistical models unidentifiable. Statistical inference is still possible when operating under the framework of partially identified models, where the goal is to bound the parameters rather than to estimate them precisely. In many matching problems, developing feasible bounds on the parameters is equivalent to finding the set of positive-definite completions of a partially specified covariance matrix. Existing methods for characterising the set of possible completions do not extend to high-dimensional problems. A Gibbs sampler to draw from the set of possible completions is proposed. The variation in the observed samples gives an estimate of the feasible region of the parameters. The Gibbs sampler extends easily to high-dimensional statistical matching problems.
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Project description:Loot boxes are items in video games that can be paid for with real-world money and contain randomised contents. In recent years, loot boxes have become increasingly common. There is concern in the research community that similarities between loot boxes and gambling may lead to increases in problem gambling amongst gamers. A large-scale survey of gamers (n = 7,422) found evidence for a link (η2 = 0.054) between the amount that gamers spent on loot boxes and the severity of their problem gambling. This link was stronger than a link between problem gambling and buying other in-game items with real-world money (η2 = 0.004), suggesting that the gambling-like features of loot boxes are specifically responsible for the observed relationship between problem gambling and spending on loot boxes. It is unclear from this study whether buying loot boxes acts as a gateway to problem gambling, or whether spending large amounts of money on loot boxes appeals more to problem gamblers. However, in either case these results suggest that there may be good reason to regulate loot boxes in games.
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