9 resultados para Social hypothesis testing

em National Center for Biotechnology Information - NCBI


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Requirements for testing include advance specification of the conditional rate density (probability per unit time, area, and magnitude) or, alternatively, probabilities for specified intervals of time, space, and magnitude. Here I consider testing fully specified hypotheses, with no parameter adjustments or arbitrary decisions allowed during the test period. Because it may take decades to validate prediction methods, it is worthwhile to formulate testable hypotheses carefully in advance. Earthquake prediction generally implies that the probability will be temporarily higher than normal. Such a statement requires knowledge of "normal behavior"--that is, it requires a null hypothesis. Hypotheses can be tested in three ways: (i) by comparing the number of actual earth-quakes to the number predicted, (ii) by comparing the likelihood score of actual earthquakes to the predicted distribution, and (iii) by comparing the likelihood ratio to that of a null hypothesis. The first two tests are purely self-consistency tests, while the third is a direct comparison of two hypotheses. Predictions made without a statement of probability are very difficult to test, and any test must be based on the ratio of earthquakes in and out of the forecast regions.

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Evolutionary trees are often estimated from DNA or RNA sequence data. How much confidence should we have in the estimated trees? In 1985, Felsenstein [Felsenstein, J. (1985) Evolution 39, 783–791] suggested the use of the bootstrap to answer this question. Felsenstein’s method, which in concept is a straightforward application of the bootstrap, is widely used, but has been criticized as biased in the genetics literature. This paper concerns the use of the bootstrap in the tree problem. We show that Felsenstein’s method is not biased, but that it can be corrected to better agree with standard ideas of confidence levels and hypothesis testing. These corrections can be made by using the more elaborate bootstrap method presented here, at the expense of considerably more computation.

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Site-directed mutagenesis and combinatorial libraries are powerful tools for providing information about the relationship between protein sequence and structure. Here we report two extensions that expand the utility of combinatorial mutagenesis for the quantitative assessment of hypotheses about the determinants of protein structure. First, we show that resin-splitting technology, which allows the construction of arbitrarily complex libraries of degenerate oligonucleotides, can be used to construct more complex protein libraries for hypothesis testing than can be constructed from oligonucleotides limited to degenerate codons. Second, using eglin c as a model protein, we show that regression analysis of activity scores from library data can be used to assess the relative contributions to the specific activity of the amino acids that were varied in the library. The regression parameters derived from the analysis of a 455-member sample from a library wherein four solvent-exposed sites in an α-helix can contain any of nine different amino acids are highly correlated (P < 0.0001, R2 = 0.97) to the relative helix propensities for those amino acids, as estimated by a variety of biophysical and computational techniques.

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Evolutionary trees are often estimated from DNA or RNA sequence data. How much confidence should we have in the estimated trees? In 1985, Felsenstein [Felsenstein, J. (1985) Evolution 39, 783-791] suggested the use of the bootstrap to answer this question. Felsenstein's method, which in concept is a straightforward application of the bootstrap, is widely used, but has been criticized as biased in the genetics literature. This paper concerns the use of the bootstrap in the tree problem. We show that Felsenstein's method is not biased, but that it can be corrected to better agree with standard ideas of confidence levels and hypothesis testing. These corrections can be made by using the more elaborate bootstrap method presented here, at the expense of considerably more computation.

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The controversy over the interpretation of DNA profile evidence in forensic identification can be attributed in part to confusion over the mode(s) of statistical inference appropriate to this setting. Although there has been substantial discussion in the literature of, for example, the role of population genetics issues, few authors have made explicit the inferential framework which underpins their arguments. This lack of clarity has led both to unnecessary debates over ill-posed or inappropriate questions and to the neglect of some issues which can have important consequences. We argue that the mode of statistical inference which seems to underlie the arguments of some authors, based on a hypothesis testing framework, is not appropriate for forensic identification. We propose instead a logically coherent framework in which, for example, the roles both of the population genetics issues and of the nonscientific evidence in a case are incorporated. Our analysis highlights several widely held misconceptions in the DNA profiling debate. For example, the profile frequency is not directly relevant to forensic inference. Further, very small match probabilities may in some settings be consistent with acquittal. Although DNA evidence is typically very strong, our analysis of the coherent approach highlights situations which can arise in practice where alternative methods for assessing DNA evidence may be misleading.

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Molecular studies have the potential to shed light on the origin of the animal phyla by providing independent estimates of the divergence times, but have been criticized for failing to account adequately for variation in rate of evolution. A method of dating divergence times from molecular data addresses the criticisms of earlier studies and provides more realistic, but wider, confidence intervals. The data are not compatible with the Cambrian explosion hypothesis as an explanation for the origin of metazoan phyla, and provide additional support for an extended period of Precambrian metazoan diversification.

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From early in the AIDS epidemic, psychosocial stressors have been proposed as contributors to the variation in disease course. To test this hypothesis, rhesus macaques were assigned to stable or unstable social conditions and were inoculated with the simian immunodeficiency virus. Animals in the unstable condition displayed more agonism and less affiliation, shorter survival, and lower basal concentrations of plasma cortisol compared with stable animals. Early after inoculation, but before the emergence of group differences in cortisol levels, animals receiving social threats had higher concentrations of simian immunodeficiency virus RNA in plasma, and those engaging in affiliation had lower concentrations. The results indicate that social factors can have a significant impact on the course of immunodeficiency disease. Socially induced changes in pituitary–adrenal hormones may be one mechanism mediating this relationship.

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Many primates, including humans, live in complex hierarchical societies where social context and status affect daily life. Nevertheless, primate learning studies typically test single animals in limited laboratory settings where the important effects of social interactions and relationships cannot be studied. To investigate the impact of sociality on associative learning, we compared the individual performances of group-tested rhesus monkeys (Macaca mulatta) across various social contexts. We used a traditional discrimination paradigm that measures an animal’s ability to form associations between cues and the obtaining of food in choice situations; but we adapted the task for group testing. After training a 55-member colony to separate on command into two subgroups, composed of either high- or low-status families, we exposed animals to two color discrimination problems, one with all monkeys present (combined condition), the other in their “dominant” and “subordinate” cohorts (split condition). Next, we manipulated learning history by testing animals on the same problems, but with the social contexts reversed. Monkeys from dominant families excelled in all conditions, but subordinates performed well in the split condition only, regardless of learning history. Subordinate animals had learned the associations, but expressed their knowledge only when segregated from higher-ranking animals. Because aggressive behavior was rare, performance deficits probably reflected voluntary inhibition. This experimental evidence of rank-related, social modulation of performance calls for greater consideration of social factors when assessing learning and may also have relevance for the evaluation of human scholastic achievement.

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The current phylogenetic hypothesis for the evolution and biogeography of fiddler crabs relies on the assumption that complex behavioral traits are assumed to also be evolutionary derived. Indo-west Pacific fiddler crabs have simpler reproductive social behavior and are more marine and were thought to be ancestral to the more behaviorally complex and more terrestrial American species. It was also hypothesized that the evolution of more complex social and reproductive behavior was associated with the colonization of the higher intertidal zones. Our phylogenetic analysis, based upon a set of independent molecular characters, however, demonstrates how widely entrenched ideas about evolution and biogeography led to a reasonable, but apparently incorrect, conclusion about the evolutionary trends within this pantropical group of crustaceans. Species bearing the set of "derived traits" are phylogenetically ancestral, suggesting an alternative evolutionary scenario: the evolution of reproductive behavioral complexity in fiddler crabs may have arisen multiple times during their evolution. The evolution of behavioral complexity may have arisen by coopting of a series of other adaptations for high intertidal living and antipredator escape. A calibration of rates of molecular evolution from populations on either side of the Isthmus of Panama suggest a sequence divergence rate for 16S rRNA of 0.9% per million years. The divergence between the ancestral clade and derived forms is estimated to be approximately 22 million years ago, whereas the divergence between the American and Indo-west Pacific is estimated to be approximately 17 million years ago.