3,094 research outputs found

    Statistical inference for the mean outcome under a possibly non-unique optimal treatment strategy

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    We consider challenges that arise in the estimation of the mean outcome under an optimal individualized treatment strategy defined as the treatment rule that maximizes the population mean outcome, where the candidate treatment rules are restricted to depend on baseline covariates. We prove a necessary and sufficient condition for the pathwise differentiability of the optimal value, a key condition needed to develop a regular and asymptotically linear (RAL) estimator of the optimal value. The stated condition is slightly more general than the previous condition implied in the literature. We then describe an approach to obtain root-nn rate confidence intervals for the optimal value even when the parameter is not pathwise differentiable. We provide conditions under which our estimator is RAL and asymptotically efficient when the mean outcome is pathwise differentiable. We also outline an extension of our approach to a multiple time point problem. All of our results are supported by simulations.Comment: Published at http://dx.doi.org/10.1214/15-AOS1384 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Evaluating the Impact of Treating the Optimal Subgroup

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    Suppose we have a binary treatment used to influence an outcome. Given data from an observational or controlled study, we wish to determine whether or not there exists some subset of observed covariates in which the treatment is more effective than the standard practice of no treatment. Furthermore, we wish to quantify the improvement in population mean outcome that will be seen if this subgroup receives treatment and the rest of the population remains untreated. We show that this problem is surprisingly challenging given how often it is an (at least implicit) study objective. Blindly applying standard techniques fails to yield any apparent asymptotic results, while using existing techniques to confront the non-regularity does not necessarily help at distributions where there is no treatment effect. Here we describe an approach to estimate the impact of treating the subgroup which benefits from treatment that is valid in a nonparametric model and is able to deal with the case where there is no treatment effect. The approach is a slight modification of an approach that recently appeared in the individualized medicine literature

    End-of-Life Inventory Problem with Phase-out Returns

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    We consider the service parts end-of-life inventory problem of a capital goods manufacturer in the final phase of its life cycle. The final phase starts as soon as the production of parts terminates and continues until the last service contract expires. Final order quantities are considered a popular tactic to sustain service fulfillment obligations and to mitigate the effect of obsolescence. In addition to the final order quantity, other sources to obtain serviceable parts are repairing returned defective items and retrieving parts from phase-out returns. Phase-out returns happen when a customer replaces an old system platform with a next generation one and returns the old product to the original equipment manufacturer (OEM). These returns can well serve the demand for service parts of other customers still using the old generation of the product. In this paper, we study the decision-making complications stemming from phase-out occurrence. We use a finite horizon Markov decision process to characterize the structure of the optimal inventory control policy. We show that the optimal policy consists of a time varying threshold level for item repair. Furthermore, we study the value of phase-out information by extending the results to cases with an uncertain phase-out quantity or an uncertain schedule. Numerical analysis sheds light on the advantages of the optimal policy compared to some heuristic policies.spare parts;end-of-life inventory management;phase-out returns

    The effects of the Lindamood Phoneme Sequencing Program on reading fluency and comprehension of at-risk first-graders

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    The primary purpose of this research study was to determine the impact of the Lindamood-Bell Phoneme Sequencing Program on phonemic awareness, reading fluency, and comprehension of at-risk first graders in one southwestern Michigan school district. In the first phase of this research, baseline data in phonemic awareness and fluency scores were collected from two different first-grade classrooms to determine which students would be chosen for the study. The final study included 32 students, 16 from the experimental school and 16 from the control school. Both schools had similar demographic populations. In the second phase of the study, data were collected on phonemic awareness and fluency scores after the Lindamoodā€“Bell Phoneme Sequencing Program was implemented with the first graders in the experimental school. In addition, comprehension scores were collected at two different times near the end of the study in order to compare reading gains in both school settings. The data indicated that there were statistically significant relationships between the Lindamoodā€“Bell Phoneme Sequencing Program and phonemic awareness. However, it was also noted that the experimental group had high phonemic awareness scores when baseline data were originally collected. There were also statistically significant relationships between the Lindamoodā€“Bell Phoneme Sequencing Program and reading fluency and comprehension. The results suggested that if students understood phonemic awareness, reading fluency would also be gained, and in turn, reading comprehension would be greater. Therefore, phonemic awareness skills would eventually lead to greater comprehension. Results supported these conclusions. Because this sample was small, the research study was considered a pilot. Further research recommendations included using the Lindamoodā€“Bell Phoneme Sequencing Program with a larger population

    Werkhandboek combizorg

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    Combizorg is makkelijk samen te vatten: Het gaat om de vragen: wie, wat, waar, waarom, wanneer en hoe? Het opzetten van het combizorgsysteem is niet in korte tijd klaar en verloopt in verschillende fasen. Systematisch meer structuur in uw bedrijf aanbrengen verbetert continu de resultaten

    Equilibrium adjustment of disequilibrium prices

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    We consider an exchange economy in which price rigidities are present. In the short run the non-numeraire commodities have a exible price level with respect to the numeraire commodity but their relative prices are mutually fixed. In the long run prices are assumed to be completely exible. For a given price level and fixed relative prices, markets can be equilibrated by means of quantity rationing on demand and supply. Keeping markets in equilibrium through rationing, we provide an adjustment process in prices and quantities converging from a trivial equilibrium with complete demand rationing on all non-numeraire markets to a Walrasian equilibrium. Along the path initially all relative prices are kept fixed and the price level is increased. Rationing schemes are adjusted to keep markets in equilibrium. Doing so the process reaches a short run equilibrium with only demand rationing and no rationing on the numeraire and at least one of the other commodities. The process allows for a downward price adjustment of non-rationed non-numeraire commodities and reaches a Walrasian equilibrium in the long run.Equilibrium Theory;market economy;Prices;Disequilibrium Theory;Rationing;economic theory

    Combizorg in de bloembollensector : overbezorgdheid of pure noodzaak?

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    Combizorgsysteem is een voorbeeld van een modern zorgsysteem, dat nauw in handen die de moderne ondernemer nodig heeft. De ervaringen in het project combizorg in de bloembollensector, waaraan 8 bedrijven uit de bollensector in het seizoen '99-2000 deelnamen, bevestigen de verwachtte gunstige effecten van het systematisch beschrijven en denken over het eigen bedrij
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