Damn Lies Research Articles

Lies, Damn Lies, and Benchmarks: An Injunction for Trustees

Most institutional investors, such as public pension funds and endowments, report their performance using biased benchmarks. The benchmarks are biased downwardly, meaning their returns tend to be less than a fair return for the market exposures and risk exhibited by the institutions’ portfolios. Significant samples of both fund types exhibit benchmark bias in the range of 1.4 to 1.7 percentage points per year. This bias enables a sizable majority of both types of funds to report outperforming their chosen benchmarks when, in fact, most <i>under</i>perform an appropriate passive-management benchmark by a wide margin. Benchmark bias masks serious agency problems in the management of institutional funds. For example, fund staff and consultants have strong incentives to justify complex, costly, multi-asset-class portfolios, for which they themselves are the benchmarkers. Trustees may feel they have no choice but to accept the benchmarking and reporting by staff and consultants, but this only perpetuates the problem. At the very least, investment trustees should step up and take control of benchmarking and performance reporting. For <i>they</i> are the ones charged with watching the watchmen.

Data, Damn Lies, and Cannabis Policy: Reefer Madness and the Methodological Crimes of the New Prohibitionists

The rapid pace of cannabis legalization in North America has provoked a backlash that is predictable and discouraging. The New Prohibitionists, distinct but related to their predecessors, the Old Prohibitionsists, have offered scholarship rife with conceptual errors, methodological flaws, and practical oversights. While their advice would likely hasten that which they seek to decrease, they overlook the costs of returning to practices associated with prohibition. To counter simplistic research interpretations and ill-considered policy, we present a critically informed research program on cannabis and crime based on previous scholarship. Our work is designed to apply replacement discourse and refocus research to withstand the tendency for justice systems to subvert, rather than embrace, reform. Cannabis legalization has been decades in the making and serious questions remain for proponents, opponents, and policymakers. Society, however, will be far worse off if the mistakes of reefer madness are repeated.

Lies, Damn Lies, and Bad Statistics?

A wide spectrum of research such as experimental, randomized trials, cohort or epidemiological studies, technical or control case reports, systematic reviews, and meta-analyses has resulted in a huge amount of publications. These studies and publications may be subject to errors due to poor application of statistical tests, which can lead to misinformation, misinterpretation, and erroneous conclusions, sometimes even considered as lies. In this article, some ideas about this issue are discussed in order to adopt new directions in the future and thus avoid lies and bad statistics.

Lies, Damn Lies, and Statistic: A Commentary.

Lies, Damn Lies, and Statistic: A Commentary.

Lies, Damn Lies, and Statistics: Why a Widely Used Sustainability Metric Fails and How to Improve It

Most of the world's major corporations now publicly report their sustainability performance for a number of key parameters, such as water use, greenhouse gas (GHG) emissions, and waste generated. The metrics most often used to track progress are “total inventory” (for example, the total liters of water used, or the total tons of GHGs emitted) and average intensity (total liters of water used per ton of product or per $1 million revenue). Because average intensity is normalized for the company's level of business activity, it is commonly presented and viewed as a measure of the company's actual year‐to‐year efficiency. But average intensity is often not a reliable measure of a company's true performance in sustainability.An improvement in efficiency requires a company to consume fewer resources or generate less waste in delivering a specified unit measure of goods or services. This article demonstrates that, although efficiency directly contributes to average intensity, the measure is influenced by a number of confounding factors that make the change in average intensity a potentially misleading indicator of improvements in efficiency. The authors present a more reliable measure of changes in efficiency—one that is likely to benefit corporate managements as well as users of sustainability data—that makes use of flexible budgeting techniques. Examples are provided that illustrate Bacardi Limited's application of the sustainability efficiency metric for external sustainability reporting.

Lies, Damn Lies, and Fake News

The Oxford Dictionaries selected post-truth as the 2016 international word of the year. This is such a preposterous recognition from a heretofore august publication that I just can't allow it to pass in silence.

Lies, Damn Lies, and Statistics

I used to call them the Left Brain and the Right Brain. They were my two roommates at the student housing during one of my remote rotations. Lars, the Right Brain, was in med school as his second career and although he was quite bright, stunningly talented at OMM and a great listener, he resisted rote memorization of pathogens and algorithms so much that although it was our fourth year, he had yet to pass Step 2 of the boards. Tim, the Left Brain, was a delightful and friendly person who listened to Audio Digest for fun and would joyfully jump in and do the blood draws at the clinic if the MA was too busy. It was from Tim that I first heard about the JNC. Specifically, he came back to our shared apartment upset because his attending was not adhering to JNC-6 guidelines about spironolactone in CHF.

Lies, Damn Lies, and Expectations: How Base Rates Inform Lie–Truth Judgments

SummaryWe are biased towards thinking that people are telling the truth. Our study represents the first test of how beliefs about the base rate of truths and lies affect this truth bias. Raters were told either 20, 50 or 80% of the speakers would be telling the truth. As the speaker delivered their statement, participants indicated moment by moment whether they thought the speaker was lying or being truthful. At the end of the statement, they made a final lie–truth judgment and indicated their confidence. While viewing the statement, base rate beliefs had an early influence, but as time progressed, all conditions showed a truth bias. In the final judgment at the end of the statement, raters were truth biased when expecting mostly truths but did not show a lie bias when expecting mostly lies. We conclude base rate beliefs have an early influence, but over time, a truth bias dominates. Copyright © 2014 John Wiley &amp; Sons, Ltd.

Lies, Damn Lies and Reclassification Statistics: Implications for Assessing New Risk Factors for Improving Fracture Risk Prediction With FRAX

Lies, Damn Lies and Reclassification Statistics: Implications for Assessing New Risk Factors for Improving Fracture Risk Prediction With FRAX

Viewpoint: Lies, Damn Lies and Statlish?

Viewpoint: Lies, Damn Lies and Statlish?

Frequentist and Bayesian Pharmacometric-Based Approaches To Facilitate Critically Needed New Antibiotic Development: Overcoming Lies, Damn Lies, and Statistics

Antimicrobial drug development has greatly diminished due to regulatory uncertainty about the magnitude of the antibiotic treatment effect. Herein we evaluate the utility of pharmacometric-based analyses for determining the magnitude of the treatment effect. Frequentist and Bayesian pharmacometric-based logistic regression analyses were conducted by using data from a phase 3 clinical trial of tigecycline-treated patients with hospital-acquired pneumonia (HAP) to evaluate relationships between the probability of microbiological or clinical success and the free-drug area under the concentration-time curve from time zero to 24 h (AUC(0-24))/MIC ratio. By using both the frequentist and Bayesian approaches, the magnitude of the treatment effect was determined using three different methods based on the probability of success at free-drug AUC(0-24)/MIC ratios of 0.01 and 25. Differences in point estimates of the treatment effect for microbiological response (method 1) were larger using the frequentist approach than using the Bayesian approach (Bayesian estimate, 0.395; frequentist estimate, 0.637). However, the Bayesian credible intervals were tighter than the frequentist confidence intervals, demonstrating increased certainty with the former approach. The treatment effect determined by taking the difference in the probabilities of success between the upper limit of a 95% interval for the minimal exposure and the lower limit of a 95% interval at the maximal exposure (method 2) was greater for the Bayesian analysis (Bayesian estimate, 0.074; frequentist estimate, 0.004). After utilizing bootstrapping to determine the lower 95% bounds for the treatment effect (method 3), treatment effect estimates were still higher for the Bayesian analysis (Bayesian estimate, 0.301; frequentist estimate, 0.166). These results demonstrate the utility of frequentist and Bayesian pharmacometric-based analyses for the determination of the treatment effect using contemporary trial endpoints. Additionally, as demonstrated by using pharmacokinetic-pharmacodynamic data, the magnitude of the treatment effect for patients with HAP is large.

The management mythbuster

The management mythbuster

Lies, Damn Lies, and Cancer Statistics

Lies, Damn Lies, and Cancer Statistics

Lies, Damn Lies, and Pre-Election Polling

In this paper we ask question: how well do pre-election polls forecast actual results of elections in United States?1 The question is interesting for a number of reasons. First, even polling data suggest about one-third of polling respondents do not believe that polls work in the best interests of general public.2 The situa tion is such that even many national governments have undertaken to restrict some aspect of pre election polling. A 1997 international survey of governments found 30 of 78 surveyed nations had some kind of ban on publication of poll results. Second, there is a strong presumption in lit erature on professional forecasting in other con texts (such as interest rate forecasting), which do not rely on sampling per se, that forecasts will be biased. There is a variety of explanations for why forecasts will be biased; one honest motivation is that pollsters may avoid reporting results from unavoidable atypical polls. Third, in literature in economics it is sometimes assumed

Lies, Damn Lies, and Manchester's Recruiting Statistics: Degeneration as an "Urban Legend" in Victorian and Edwardian Britain

Few historians have attempted to discuss British medicine, health and welfare policies, or the biological sciences around 1900 without due reference to the concept of degeneration. Most tie public concern with degeneration to a specific set of military recruiting figures, which stated that of 11,000 would-be volunteers in Manchester, 8,000 had to be turned away due to physical defects. Further, most histories point out that these figures had a direct influence on the formation of the Inter-Departmental Committee on Physical Deterioration in 1904. With its absolute denial of hereditary decline, the 1904 Report acts as a dénouement of degenerationist fears in Britain. No historian has sought to contextualize these recruiting figures: Where did they come from? How did Manchester react? What role did that city play in the subsequent 1904 Report? Far from being the epitome of urban decay, the 1904 Report repeatedly hails Manchester as a glowing example of innovative urban reform. This article contextualizes the recruiting figures and explores how Manchester had been tackling the three key problems of Physical Deterioration-diet, exercise, and alcohol-for thirty years prior to the 1904 Report. By discussing Manchester, a new understanding of degeneration is outlined; as slogan, rhetorical tool, and urban legend, degeneration was largely feminized and domesticated. Military/masculine problems such as the recruiting figures were the exception, not the rule.

Lies, Damn Lies, and Pseudoscience: The Selling of Eye Movement Desensitization and Reprocessing (EMDR)

Lies, Damn Lies, and Pseudoscience: The Selling of Eye Movement Desensitization and Reprocessing (EMDR)

Lies, Damn Lies, and Statistics

Marian Medical Center, Santa Maria, California. magoozer@aol.comMark Twain may have overstated his distrust of statistics, but the issue of interpretation of statistics comes to the forefront in the study by Arbous et al. 1and the accompanying editorial by Warner.2As the results of the study are discussed, Arbous et al. jump from describing associations between outcomes and management factors, to cause-and-effect descriptions: “it was found … a checklist decreased the risk,”“the reversal of the effect of opiates and muscle relaxants seems to decrease the risk,” and so on. Warner embraces these ersatz “risks” as showing “anesthetic management processes to dramatically reduce perioperative mortality.”When one looks at baseline characteristics of the study and control groups, there are, as the authors note, huge differences in the categories of urgent/emergent nature, time of day procedure performed, and American Society of Anesthesiologists physical status. In fact, 40% of the study cases were rated American Society of Anesthesiologists V—not expected to survive for 24 h, with or without surgery (regardless of anesthetic management). If we accept that a large proportion of the study cases carry greater risk by virtue of their physical status and the emergent nature of the injury or disease process, and that urgent/emergent cases generally account for all the outside working hour cases, differences in anesthetic management processes between the two groups seem more coincidentally associated than causative. Were equipment checks performed less frequently in the study group because of the emergent nature of the cases? Was the lower percentage of two providers at termination of a procedure simply a function of the outside hour the procedure was performed? Was the lower reversal rate of opiates and muscle relaxants due to the fact that the study group was sicker, undergoing more complex procedures, and so remained intubated postoperatively? Did the study groups receive fewer narcotics and local anesthetics for postoperative pain because of their moribund (comatose?) or unstable condition?This is not to suggest that anesthesia practice factors do not affect morbidity and mortality; some of the anesthetic practice factors in this study may one day be proven to be causative. But let us appreciate the method of this study for what it is: a tool to identify associations. Those associations then need to be further studied to identify them as causative or coincidental. Cars manufactured on Monday do not have more problems than others because that day of the week starts with the letter M . We need to look for truths, damn truths, and more than associations.Marian Medical Center, Santa Maria, California. magoozer@aol.com

Books

Toxic Sludge Is Good for You: Lies, Damn Lies, and the Public Relations Industry, by John Stauber and Sheldon RamptonGreenwash: The Reality behind Corporate Environ‐mentalism, by Jed Greer and Kenny Bruno.

Lies, damn lies, and reference intervals (or hysterical control values for clinical pathology data)

Lies, damn lies, and reference intervals (or hysterical control values for clinical pathology data)

The new social contract: America's journey from welfare state to police state

Introduction Poverty Urban Riots and the Beginning of the New Social Contract The Restoration of Order and the Reduction in Social Provision: Poverty in the 1990s The New Homelessness: The Reagan Legacy Crime The Explosion of the Criminal Justice System: The Muscle of the New Social Contract The F.B.I.'s Dirty Little Secret: Lies, Damn Lies, and Statistics The Media and Public Hysteria About Crime Legal Change Assault on the Constitution: Penal Code Reforms Assault on the Constitution: The Death of the Fourth Amendment The End of the War on Drugs Conclusion The New Social Contract Notes Index