Regression zur Mitte

Die Rehabilitation (Impact Factor: 0.73). 08/2005; 44(04):244-251. DOI: 10.1055/s-2005-866924
Download full-text


Available from: Markus Wirtz, May 06, 2014
298 Reads
  • Source
    • "Medical rehabilitation programmes for example, often are evaluated for their ability to restore the patient's ability to work. Unaware of RTM effects a patient's recovery typically is interpreted as a treatment effect [2]. Other examples include the evaluation of asthma disease management programmes [3] or cholesterol screening [4]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Regression to the mean (RTM) occurs in situations of repeated measurements when extreme values are followed by measurements in the same subjects that are closer to the mean of the basic population. In uncontrolled studies such changes are likely to be interpreted as a real treatment effect. Several statistical approaches have been developed to analyse such situations, including the algorithm of Mee and Chua which assumes a known population mean mu. We extend this approach to a situation where mu is unknown and suggest to vary it systematically over a range of reasonable values. Using differential calculus we provide formulas to estimate the range of mu where treatment effects are likely to occur when RTM is present. We successfully applied our method to three real world examples denoting situations when (a) no treatment effect can be confirmed regardless which mu is true, (b) when a treatment effect must be assumed independent from the true mu and (c) in the appraisal of results of uncontrolled studies. Our method can be used to separate the wheat from the chaff in situations, when one has to interpret the results of uncontrolled studies. In meta-analysis, health-technology reports or systematic reviews this approach may be helpful to clarify the evidence given from uncontrolled observational studies.
    BMC Medical Research Methodology 02/2008; 8:52. DOI:10.1186/1471-2288-8-52 · 2.27 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: NAND flash memory has become an indispensable component in mobile embedded systems because of its versatile features such as nonvolatility, solid-state reliability, low cost and high density. Even though NAND flash memory is gaining popularity as data storage, it can be also exploited as code memory for XIP (execute-in-place). In this paper, we present a new memory architecture in which incorporates NAND flash memory into an existing memory hierarchy for code execution. The usefulness of the proposed approach is demonstrated with real embedded workloads on a real prototyping board.
    Hardware/Software Codesign and System Synthesis, 2003. First IEEE/ACM/IFIP International Conference on; 11/2003
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The role of placebos is often misunderstood, leading both to overvaluation and to inappropriate disdain. The effect of a placebo that contains no pharmacologically active substance is often confused with the effect of administration by a physician. The aim of this article is to review the current data on placebos, evaluate these data critically, and provide a well-founded and understandable explanation of the effects that placebos do and do not possess. Selective literature review. Recent studies employing modern imaging techniques have provided objective correlates of the effect of placebo administration for certain indications. A recent paper even suggested a genetic basis for it. Two main mechanisms underlie the effect of placebo administration: conditioned reflexes, which are subconscious, and the patient's expectations, which are conscious. Further factors include the physician's personality and the setting in which the treatment takes place. The mechanisms of action of placebo administration, with which positive therapeutic effects can be achieved with little effort, should be consciously exploited by physicians when giving their patients pharmacologically active medications as well.
    Deutsches Ärzteblatt International 11/2009; 106(46):751-5. DOI:10.3238/arztebl.2009.0751 · 3.52 Impact Factor