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51.
The Value of Information in Decision‐Analytic Modeling for Malaria Vector Control in East Africa 下载免费PDF全文
Dohyeong Kim Zachary Brown Richard Anderson Clifford Mutero Marie Lynn Miranda Jonathan Wiener Randall Kramer 《Risk analysis》2017,37(2):231-244
Decision analysis tools and mathematical modeling are increasingly emphasized in malaria control programs worldwide to improve resource allocation and address ongoing challenges with sustainability. However, such tools require substantial scientific evidence, which is costly to acquire. The value of information (VOI) has been proposed as a metric for gauging the value of reduced model uncertainty. We apply this concept to an evidenced‐based Malaria Decision Analysis Support Tool (MDAST) designed for application in East Africa. In developing MDAST, substantial gaps in the scientific evidence base were identified regarding insecticide resistance in malaria vector control and the effectiveness of alternative mosquito control approaches, including larviciding. We identify four entomological parameters in the model (two for insecticide resistance and two for larviciding) that involve high levels of uncertainty and to which outputs in MDAST are sensitive. We estimate and compare a VOI for combinations of these parameters in evaluating three policy alternatives relative to a status quo policy. We find having perfect information on the uncertain parameters could improve program net benefits by up to 5–21%, with the highest VOI associated with jointly eliminating uncertainty about reproductive speed of malaria‐transmitting mosquitoes and initial efficacy of larviciding at reducing the emergence of new adult mosquitoes. Future research on parameter uncertainty in decision analysis of malaria control policy should investigate the VOI with respect to other aspects of malaria transmission (such as antimalarial resistance), the costs of reducing uncertainty in these parameters, and the extent to which imperfect information about these parameters can improve payoffs. 相似文献
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Peter Brown Yuedong Yang Yaoqi Zhou Wayne Pullan 《Journal of Combinatorial Optimization》2017,33(2):551-566
The linear sum assignment problem is a fundamental combinatorial optimisation problem and can be broadly defined as: given an \(n \times m, m \ge n\) benefit matrix \(B = (b_{ij})\), matching each row to a different column so that the sum of entries at the row-column intersections is maximised. This paper describes the application of a new fast heuristic algorithm, Asymmetric Greedy Search, to the asymmetric version (\(n \ne m\)) of the linear sum assignment problem. Extensive computational experiments, using a range of model graphs demonstrate the effectiveness of the algorithm. The heuristic was also incorporated within an algorithm for the non-sequential protein structure matching problem where non-sequential alignment between two proteins, normally of different numbers of amino acids, needs to be maximised. 相似文献
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Richard Margoluis Caroline Stem Nick Salafsky Marcia Brown 《Evaluation and program planning》2009,32(2):138-147
Conservation projects are dynamic interventions that occur in complex contexts involving intricate interactions of social, political, economic, cultural, and environmental factors. These factors are constantly changing over time and space as managers learn more about the context within which they work. This complex context poses challenges for planning and evaluating conservation project. In order for conservation managers and evaluation professionals to design good interventions and measure project success, they simultaneously need to embrace and deconstruct contextual complexity.In this article, we describe conceptual models—a tool that helps articulate and make explicit assumptions about a project's context and what a project team hopes to achieve. We provide real-world examples of conceptual models, discuss the relationship between conceptual models and other evaluation tools, and describe various ways that conceptual models serve as a key planning and evaluation tool. These include, for example, that they document assumptions about a project site and they provide a basis for analyzing theories of change.It is impractical to believe that we can completely eliminate detail or dynamic complexity in projects. Nevertheless, conceptual models can help reduce the effects of this complexity by helping us understand it. 相似文献
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Techniques used in variability assessment are subsequently used to draw conclusions regarding the “spread”/uniformity of data curves. Due to the limitations of these techniques, they are not adequate for circumstances where data manifest with multiple peaks. Examples of these manifestations (in three-dimensional space) include under-foot pressure distributions recorded for different types of footwear (Becerro-de-Bengoa-Vallejo et al., 2014; Cibulka et al., 1994; Davies et al., 2003), surface textures and interfaces designed to impact friction, and and and molecular surface structures such as viral epitopes (Torras and Garcia-Valls, 2004; Pacejka, 1997; Fustaffson, 1997). This article proposes a technique for generating a single variable – Λ that will quantify the uniformity of such surfaces. We define and validate this technique using several mathematical and graphical models. 相似文献
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One in five students report experimenting with tobacco before the age of 13 and most prevention efforts take place in the school setting. This study measures the effect of a single-lesson tobacco prevention curriculum, conducted by a health education center, focusing on knowledge of tobacco, ability to identify refusal techniques, and intent not to smoke. Data were collected, via electronic keypads, from students visiting a non-school, health education center in Michigan (n = 704 intervention and 85 comparison). Contingency table Chi-squared tests and t-tests demonstrated that a single lesson can improve general knowledge and ability to identify appropriate refusal techniques. Improvement in intent not to smoke was not significant because both groups had very high intent prior to implementation. Similar to results from other programs, multivariate logistic regression of gender, general knowledge, and skill identification revealed that only the skill variable was associated with intent not to smoke at pretest. Recommendations are given for further research and for designing more effective curricula or programs. 相似文献
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Davis LW Strasburger AM Brown LF 《Journal of psychosocial nursing and mental health services》2007,45(11):23-29
Despite evidence that individuals with schizophrenia spectrum disorders experience significant and persistent symptoms of anxiety, there are few reports of the use of empirically supported treatments for anxiety in this population. This article describes how we have tried to adapt mindfulness interventions to help individuals with schizophrenia who experience significant anxiety symptoms. Although mindfulness has been widely used to help individuals without psychosis, to our knowledge, this is the first study adapting it to help those with schizophrenia manage worry and stress. We provide an overview of the intervention and use an individual example to describe how our treatment development group responded. We also explore directions for future research of mindfulness interventions for schizophrenia. 相似文献
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Statistical experiments, more commonly referred to as Monte Carlo or simulation studies, are used to study the behavior of statistical methods and measures under controlled situations. Whereas recent computing and methodological advances have permitted increased efficiency in the simulation process, known as variance reduction, such experiments remain limited by their finite nature and hence are subject to uncertainty; when a simulation is run more than once, different results are obtained. However, virtually no emphasis has been placed on reporting the uncertainty, referred to here as Monte Carlo error, associated with simulation results in the published literature, or on justifying the number of replications used. These deserve broader consideration. Here we present a series of simple and practical methods for estimating Monte Carlo error as well as determining the number of replications required to achieve a desired level of accuracy. The issues and methods are demonstrated with two simple examples, one evaluating operating characteristics of the maximum likelihood estimator for the parameters in logistic regression and the other in the context of using the bootstrap to obtain 95% confidence intervals. The results suggest that in many settings, Monte Carlo error may be more substantial than traditionally thought. 相似文献