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Legal Frameworks, Normative Action and Performance of Biosocial Projects in Informal Settlements in Nairobi County, Kenya

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This book is written for individuals interested in understanding the Research process. It is a very simplified book and written in a didactic manner for easy of understanding the content.
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A general theory of heritable personality traits and their neurobiological basis is described. Three independent dimensions of personality are defined and related to heritable variation in patterns of response to specific types of environmental stimuli: 'novelty seeking' is due to a heritable tendency toward frequent exploratory activity and intense excitement in response to novel stimuli; 'harm avoidance' is due to a heritable tendency to respond intensely to aversive stimuli and to learn to avoid punishment, novelty, and non-reward passively; and 'reward dependence' is due to a heritable tendency to respond intensely to reward and succorance and to learn to maintain rewarded behavior. Evidence suggests that variation in each dimension is strongly correlated with activity in a specific central monoaminergic pathway: novelty seeking with low basal dopaminergic activity, harm avoidance with high serotonergic activity, and reward dependence with low basal noradrenergic activity. These neurobiological dimensions interact to give rise to integrated patterns of differential responses to punishment, reward, and novelty. The combination of high novelty seeking, high reward dependence, and low harm avoidance (histrionic personality) or the combination of high harm avoidance, low reward dependence, and low novelty seeking (obsessional personality) are each associated with information-processing patterns that lead to unreliable discrimination of safe and dangerous situations and hence to chronic anxiety. In individuals with high novelty seeking, chronic anxiety is characterized by global uneasiness or alarm without specific premonitory cues, frequent bodily pains due to low pain and sensation thresholds, low sedation threshold, and slow fatigability. In contrast, in individuals with high harm avoidance, chronic anxiety is characterized by frequent anticipatory worries based on specific cues, high pain and sedation thresholds, and easy fatigability. In response to frustrative non-reward, individuals with high reward dependence are susceptible to compensatory noradrenergic hyperactivity and hence acute or recurrent states of agitated dysphoria associated with reward-seeking behaviors such as overeating and increased sexual activity. Specific predictions are made about normal personality development as well as the development and familial aggregation of anxiety, somatoform, depressive and personality disorders. These predictions are compared with available information, and recommendations are made for future research.
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The authors studied social norms and prejudice using M. Sherif and C. W. Sherif's (1953) group norm theory of attitudes. In 7 studies (N = 1,504), social norms were measured and manipulated to examine their effects on prejudice; both normatively proscribed and normatively prescribed forms of prejudice were included. The public expression of prejudice toward 105 social groups was very highly correlated with social approval of that expression. Participants closely adhere to social norms when expressing prejudice, evaluating scenarios of discrimination, and reacting to hostile jokes. The authors reconceptualized the source of motivation to suppress prejudice in terms of identifying with new reference groups and adapting oneself to fit new norms. Suppression scales seem to measure patterns of concern about group norms rather than personal commitments to reducing prejudice; high suppressors are strong norm followers. Compared with low suppressors, high suppressors follow normative rules more closely and are more strongly influenced by shifts in local social norms. There is much value in continuing the study of normative influence and self-adaptation to social norms, particularly in terms of the group norm theory of attitudes.
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The Book is the Italian Edition of M-M: Linehan DBT skills training manual pp.900
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Likert-type data are often assumed to be equidistant by applied researchers so that they can use parametric methods to analyse the data. Since the equidistance assumption rarely is tested, the validity of parametric analyses of Likert-type data is often unclear. This paper consists of two parts where we deal with this validity problem in two different respects. In the first part, we use an experimental design to show that the perceived distance between scale points on a regular five-point Likert-type scale depends on how the verbal anchors are used. Anchors only at the end points create a relatively larger perceived distance between points near the ends of the scale than in the middle (end-of-scale effect), while anchors at all points create a larger perceived distance between points in the middle of the scale (middle-of-scale effect). Hence, Likert-type scales are generally not perceived as equidistant by subjects. In the second part of the paper, we use Monte Carlo simulations to explore how parametric methods commonly used to compare means between several groups perform in terms of actual significance and power when data are assumed to be equidistant even though they are not. The results show that the preferred statistical method to analyse Likert-type data depends on the nature of their nonequidistance as well as their skewness. Under middle-of-scale effect, the omnibus one-way ANOVA works best when data are relatively symmetric. However, the Kruskal-Wallis test works better when data are skewed except when sample sizes are unequal, in which case the Brown-Forsythe test is better. Under end-of-scale effect, on the other hand, the Kruskal- Wallis test should be preferred in most cases when data are at most moderately skewed. When data are heavily skewed, ANOVA works best unless when sample sizes are unequal, in which case the Brown-Forsythe test should be preferred.
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The clear and practical writing of Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Researchhas made this book a favorite. In precise step-by-step language the book helps you learn how to conduct, read, and evaluate research studies. Key changes include: expanded coverage of ethics and new research articles.
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We address the problem of heavy noise conditions in optimal multivariate joint-analysis between finite, one-dimensional stochastic processes, as a measure for similarity between the random variables. By introducing low-order statistical moment estimations of the additive noise components to the method of multivariate ordinary and canonical correlation analysis, we determine the strength of the correlations between the stochastic variables even under heavy noise conditions. The new method is based on high-order stochastic differentiations of the involved signals, and the correlations derived by the proposed method are compared to covariance correlation analysis and to rank correlation techniques. It is shown that the new method is capable of extracting the correlation coefficient between two sets of stochastic variables even when the noise levels in the individual sets are significant and in situations where canonical correlation analysis reports on degraded correlation values due to the heavy noise contributions. It is shown that the expressions for the proposed correlation coefficient can be separated into a deterministic and a stochastic component and that the new method is a generalization of the canonical correlation analysis and converges to the conventional expressions when the noise components approach zero. An additional purpose of the present paper is to further consider the case of different, dynamic noise levels in the analyzed signals and to propose an alternative criterion for the non-stationary pair-wise correlations within the statistical characteristics of the analyzed signals.
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Objectives IntroductionThe Chi-Square Goodness-of-Fit TestThe Chi-Square Test for IndependenceThe Fisher Exact TestExamples from the LiteratureSummaryPractice QuestionsSolutions to Practice Questions
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Prescriptive research is at the heart of the project management (PM) disciplines. For decades, researchers and practitioners alike have been searching for methodological solutions to practical project management problems. Scheduling methods or risk management methodologies are just two examples. Despite this long tradition of prescriptive research, PM methods suffer from a number of problems, such as a lack of acceptance in practice, limited effectiveness, and unclear application scenarios. In this article, we identify a lack of empirical and theoretical foundations as one cause of these deficiencies. Based on a review of existing PM literature and a thorough analysis of other successful prescriptive disciplines, we develop a framework designed to serve as a guideline for theoretically grounded prescriptive PM research. The framework outlines how theories and empirical investigations can help build applicable and useful prescriptive research results. We illustrate our framework by applying it to the case of the critical chain method. Our contribution is twofold: our research results can foster the discourse on methodological support for prescriptive PM research; it may also help set up viable prescriptive research designs.