10 resultados para Binary hypothesis testing

em Aston University Research Archive


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We discuss aggregation of data from neuropsychological patients and the process of evaluating models using data from a series of patients. We argue that aggregation can be misleading but not aggregating can also result in information loss. The basis for combining data needs to be theoretically defined, and the particular method of aggregation depends on the theoretical question and characteristics of the data. We present examples, often drawn from our own research, to illustrate these points. We also argue that statistical models and formal methods of model selection are a useful way to test theoretical accounts using data from several patients in multiple-case studies or case series. Statistical models can often measure fit in a way that explicitly captures what a theory allows; the parameter values that result from model fitting often measure theoretically important dimensions and can lead to more constrained theories or new predictions; and model selection allows the strength of evidence for models to be quantified without forcing this into the artificial binary choice that characterizes hypothesis testing methods. Methods that aggregate and then formally model patient data, however, are not automatically preferred to other methods. Which method is preferred depends on the question to be addressed, characteristics of the data, and practical issues like availability of suitable patients, but case series, multiple-case studies, single-case studies, statistical models, and process models should be complementary methods when guided by theory development.

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Spectral and coherence methodologies are ubiquitous for the analysis of multiple time series. Partial coherence analysis may be used to try to determine graphical models for brain functional connectivity. The outcome of such an analysis may be considerably influenced by factors such as the degree of spectral smoothing, line and interference removal, matrix inversion stabilization and the suppression of effects caused by side-lobe leakage, the combination of results from different epochs and people, and multiple hypothesis testing. This paper examines each of these steps in turn and provides a possible path which produces relatively ‘clean’ connectivity plots. In particular we show how spectral matrix diagonal up-weighting can simultaneously stabilize spectral matrix inversion and reduce effects caused by side-lobe leakage, and use the stepdown multiple hypothesis test procedure to help formulate an interaction strength.

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This research sets out to assess if the PHC system in rural Nigeria is effective by testing the research hypothesis: `PHC can be effective if and only if the Health Care Delivery System matches the attitudes and expectations of the Community'. The field surveys to accomplish this task were carried out in IBO, YORUBA, and HAUSA rural communities. A variety of techniques have been used as Research Methodology and these include questionnaires, interviews and personal observations of events in the rural community. This thesis embraces three main parts. Part I traces the socio-cultural aspects of PHC in rural Nigeria, describes PHC management activities in Nigeria and the practical problems inherent in the system. Part II describes various theoretical and practical research techniques used for the study and concentrates on the field work programme, data analysis and the research hypothesis-testing. Part III focusses on general strategies to improve PHC system in Nigeria to make it more effective. The research contributions to knowledge and the summary of main conclusions of the study are highlighted in this part also. Based on testing and exploring the research hypothesis as stated above, some conclusions have been arrived at, which suggested that PHC in rural Nigeria is ineffective as revealed in people's low opinions of the system and dissatisfaction with PHC services. Many people had expressed the view that they could not obtain health care services in time, at a cost they could afford and in a manner acceptable to them. Following the conclusions, some alternative ways to implement PHC programmes in rural Nigeria have been put forward to improve and make the Nigerian PHC system more effective.

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Citation information: Armstrong RA, Davies LN, Dunne MCM & Gilmartin B. Statistical guidelines for clinical studies of human vision. Ophthalmic Physiol Opt 2011, 31, 123-136. doi: 10.1111/j.1475-1313.2010.00815.x ABSTRACT: Statistical analysis of data can be complex and different statisticians may disagree as to the correct approach leading to conflict between authors, editors, and reviewers. The objective of this article is to provide some statistical advice for contributors to optometric and ophthalmic journals, to provide advice specifically relevant to clinical studies of human vision, and to recommend statistical analyses that could be used in a variety of circumstances. In submitting an article, in which quantitative data are reported, authors should describe clearly the statistical procedures that they have used and to justify each stage of the analysis. This is especially important if more complex or 'non-standard' analyses have been carried out. The article begins with some general comments relating to data analysis concerning sample size and 'power', hypothesis testing, parametric and non-parametric variables, 'bootstrap methods', one and two-tail testing, and the Bonferroni correction. More specific advice is then given with reference to particular statistical procedures that can be used on a variety of types of data. Where relevant, examples of correct statistical practice are given with reference to recently published articles in the optometric and ophthalmic literature.

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Although considerable effort has been invested in the measurement of banking efficiency using Data Envelopment Analysis, hardly any empirical research has focused on comparison of banks in Gulf States Countries This paper employs data on Gulf States banking sector for the period 2000-2002 to develop efficiency scores and rankings for both Islamic and conventional banks. We then investigate the productivity change using Malmquist Index and decompose the productivity into technical change and efficiency change. Further, hypothesis testing and statistical precision in the context of nonparametric efficiency and productivity measurement have been used. Specially, cross-country analysis of efficiency and comparisons of efficiencies between Islamic banks and conventional banks have been investigated using Mann-Whitney test.

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The incentive dilemma refers to a situation in which incentives are offered but do not work as intended. The authors suggest that, in an interorganizational context, whether a principal-provided incentive works is a function of how it is evaluated by an agent: for its contribution to the agent's bottom line (instrumental evaluation) and for the extent it is strategically aligned with the agent's direction (congruence evaluation). To further understand when incentives work, the influence of two key contextual variables-industry volatility and dependence-are examined. A field study featuring 57 semi-structured depth interviews and 386 responses from twin surveys in the information technology and brewing industries provide data for hypothesis testing. When and whether incentives work is demonstrated by certain conditions under which the agent's evaluation of an incentive has positive or negative effects on its compliance and active representation. Further, some outcomes are reversed in the high volatility condition. © 2013 Academy of Marketing Science.

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This work attempts to shed light to the fundamental concepts behind the stability of Multi-Agent Systems. We view the system as a discrete time Markov chain with a potentially unknown transitional probability distribution. The system will be considered to be stable when its state has converged to an equilibrium distribution. Faced with the non-trivial task of establishing the convergence to such a distribution, we propose a hypothesis testing approach according to which we test whether the convergence of a particular system metric has occurred. We describe some artificial multi-agent ecosystems that were developed and we present results based on these systems which confirm that this approach qualitatively agrees with our intuition.

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We agree with de Jong et al.'s argument that business historians should make their methods more explicit and welcome a more general debate about the most appropriate methods for business historical research. But rather than advocating one ‘new business history’, we argue that contemporary debates about methodology in business history need greater appreciation for the diversity of approaches that have developed in the last decade. And while the hypothesis-testing framework prevalent in the mainstream social sciences favoured by de Jong et al. should have its place among these methodologies, we identify a number of additional streams of research that can legitimately claim to have contributed novel methodological insights by broadening the range of interpretative and qualitative approaches to business history. Thus, we reject privileging a single method, whatever it may be, and argue instead in favour of recognising the plurality of methods being developed and used by business historians – both within their own field and as a basis for interactions with others.

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This paper presents a fast part-based subspace selection algorithm, termed the binary sparse nonnegative matrix factorization (B-SNMF). Both the training process and the testing process of B-SNMF are much faster than those of binary principal component analysis (B-PCA). Besides, B-SNMF is more robust to occlusions in images. Experimental results on face images demonstrate the effectiveness and the efficiency of the proposed B-SNMF.

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This study investigated whether Negative Affectivity (NA) causes bias in self-report measures of activity limitations or whether NA has a real, non-artifactual association with activity limitations. The Symptom Perception Hypothesis (NA negatively biases self-reporting), Disability Hypothesis (activity limitations cause NA) and Psychosomatic Hypothesis (NA causes activity limitations) were examined longitudinally using both self-report and objective activity limitations measures. Participants were 101 stroke patients and their caregivers interviewed within two weeks of discharge, six weeks later and six months post-discharge. NA and self-report, proxy-report and observed performance activity (walking) limitations were assessed at each interview. NA was associated with activity limitations across measures. Both the Disability and Psychosomatic Hypotheses were supported: initial NA predicted objective activity limitations at six weeks but, additionally, activity limitations at six weeks predicted NA at six months. These results suggest that NA both affects and is affected by activity limitations and does not simply influence reporting.