967 research outputs found

    How Much of CAM Is Based on Research Evidence?

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    The aim of this article is to provide a preliminary estimate of how much CAM is evidence-based. For this purpose, I calculated the percentage of 685 treatment/condition pairings evaluated in the “Desktop Guide to Complementary and Alternative Medicine” which are supported by sound data. The resulting figure was 7.4%. For a range of reasons, it might be a gross over-estimate. Further investigations into this subject are required to arrive at more representative figures

    Equivalence and Non-inferiority Trials of CAM

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    THOU SHALL NOT BRUSH YOUR TEETH WHILE EATING BREAKFAST: A 7- STEP PROGRAM FOR RESEARCHERS PREVIOUSLY HURT IN DATA ANALYSIS

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    After years of providing statistical advice to fellow faculty members and graduate students, I have come to realize that it is not necessarily the big issues, but lack of knowledge of basic data analysis principles that get my clients into trouble. My claim is that if researchers and students internalized two basic definitions they would not have any problems analyzing most of their experiments. The definitions of Experimental Unit (EU) as the smallest physical unit to which a treatment may be applied and Experimental Error (Exp. Err.) as the variation among EUs treated alike are the basis for successful data analysis of experiments. I follow a seven-step data analysis program for my graduate student and faculty clients: (1) Understanding the experiment; (2) Checking the data; (3) Getting a feel for the data; (4) Checking underlying assumptions; (5) Testing; (6) Estimating; and (7) Interpreting results. Clients who have adhered to the program generally have had fewer problems than clients who, for some reason or another, did not get on board of the program. I will also touch on the implications for teaching experimental design and data analysis to non-statistics majors

    The Gnostic Myth: Protology

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    L’estudi presenta les característiques essencials de la protologia gnòstica. En fer-ho, es presenten les tendències de la recerca actual, les quals miren d’evitar generalment el terme «Gnosis», i volen entendre la correlació dels fenòmens com indicis del primitiu judaisme o del misticisme del primer cristianisme.The study presents essential characteristics of Gnostic protology. In doing so, it discusses currents of present Gnosis research which generally try to avoid the term “Gnosis” and want to understand correlating phenomena as traces of early Jewish or early Christian mysticism

    Dismantling yhe rhetoric of alternative medicine : smokescreens, errors, conspiracies, and follies

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    Alternative medicine has a high social prevalence, being promoted by well organized groups that have developed an intricate rhetoric in order to self-justify in the absence of evidence. This article will analyse some of these arguments, some of their fallacies ??ad populum, ad ignorantiam??, other styles of reasoning ??conspiracy theories?? and other misconceptions of scientific concepts ??placebo effect, scientific authority. The objective will be to highlight the poverty of the rhetoric of proponents of alternative medicine, with special emphasis on the dangers for the consumer

    Why homoeopathy is pseudoscience

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    Homoeopathy is commonly recognised as pseudoscience. However, there is, to date, no systematic discussion that seeks to establish this view. In this paper, we try to fill this gap. We explain the nature of homoeopathy, discuss the notion of pseudoscience, and provide illustrative examples from the literature indicating why homoeopathy fits the bill. Our argument contains a conceptual and an empirical part. In the conceptual part, we introduce the premise that a doctrine qualifies as a pseudoscience if, firstly, its proponents claim scientific standing for it and, secondly, if they produce bullshit to defend it, such that, unlike science, it cannot be viewed as the most reliable knowledge on its topic. In the empirical part, we provide evidence that homoeopathy fulfils both criteria. The first is quickly established since homoeopaths often explicitly claim scientificity. To establish the second, we dive into the pseudo-academic literature on homoeopathy to provide evidence of bullshit in the arguments of homoeopaths. Specifically, we show that they make bizarre ontological claims incompatible with natural science, illegitimately shift the burden of proof to sceptics, and mischaracterise, cherry-pick, and misreport the evidence. Furthermore, we demonstrate that they reject essential parts of established scientific methodology and use epistemically unfair strategies to immunise their doctrine against recalcitrant evidence

    ARMedAND DANGEROUS: THE CONSEQUENCES OF NOT RANDOMIZING THE FIRST BLOCK

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    Replication and randomization and are the keys for statistically valid experiments. Both are necessary components for statistically valid experimentation. Yet it is an industry wide practicein weed science research to assign treatment in the first block of a randomized complete block design in a systematic order for reasons of convenience. We investigated this practice by comparing four randomization/analysis scenarios: (i) complete randomization in all blocks, (ii) systematic assignment of treatmentsin block 1, where the best treatment was assigned to the best plot, (iii) systematic assignment of treatmentsin block 1, where the best treatment was assigned to the worst plot,and (iv) systematic assignment of reatments in block 1 but not using it in the analysis. We created 1000 simulated datasets for three levels of experimental precision and two group sizes (t=3 and t=9). Results indicate that dropping block 1 from the analysis resulted in a loss of power, as did the best to worst assignment scenario. The best to best assignment resulted in increased power that would lead to an inflated Type I error. Differences between the drop block 1 and best to worst scenarios tended to become smaller as the experiment size increased and the experimental precision decreased. The recommendation for the practice would be (1) to follow proper randomization procedures, and (2) to add an extra block to the experiment for demonstration purposes only
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