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    Quasi-Experimental Methods

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    A quasi-experiment is a research method in which the experimenter uses preexisting differences between participants rather than random assignment to allocate the participants to different conditions of the study. An example of a quasi-experiment is a comparison between the behavior of children at high risk and at low risk of autism spectrum disorder. The first condition corresponds to children who have an older brother or sister who has received a clinical diagnosis of an autism spectrum disorder from expert clinicians. The second condition corresponds to children who do not have an older brother or sister with autism spectrum disorder. For objective reasons, the researcher cannot assign the two conditions to all the participants. Sometimes, researchers cannot randomly assign the participants to the experimental conditions for ethical reasons. For example, let us assume a researcher is aiming to evaluate the effects of malnutrition on child development. To achieve this aim, one group of children will receive the recommended amount of food per day, while the other group will not receive enough food. The researcher then measures the children’s growth curves in the two groups. However, in this case, the researcher must face the dilemma of deciding how to select the group that will receive the recommended amount of food versus the malnourished group. Naturally, no researcher has the right to take on such a responsibility. Therefore, the best way to solve this ethical dilemma is to apply a quasi-experimental design in which naturally fooddeprived children are compared with children living in different conditions. In other cases, researchers cannot assign participants to an experimental condition for practical reasons. For example, if we want to study the effects of supplementary water consumption at school on children’s cognitive performance, it is difficult to assign pupils within the same class to different conditions. In such a case, it is more practical to consider the whole class a unit, to administer supplementary water to a group of classes, and then to compare the cognitive performance of those classes with those that did not receive supplementary water during the school day. As a consequence of the fact that it is impossible to assign participants randomly to the conditions of a study, any differences in the dependent variables between the groups may be due not just to manipulation of the independent variables but also to several other factors that differ between the groups. For example, if we identify differences between males and females in relation to disgust sensitivity, these differences may be due to neurobiological factors, for example, the activation of different brain circuits in response to disgust elicitors, differences in educational history, or cultural factors. Thus, further research is needed to explore alternative explanations. Usually, these alternative explanations are not determined by logic; rather, researchers consider the most relevant ones according to the field of study. A focus of the study of development is how behavior changes over time. Chronological age is the variable most used to operationalize changes in relation to time. Because experimenters cannot assign chronological age randomly to their participants, quasi-experimental methods offer a unique opportunity to investigate changes in the course of human development. Researchers mainly use quasi-experimental design to explore the following: (a) differences between preselected groups at the same chronological age, (b) comparisons between groups characterized by different chronological ages, and (c) differences in the same group of participants at different chronological ages. This entry provides a description of three main quasi-experimental designs that explore these differences, namely, nonequivalent control group design, cross-sectional design, and longitudinal design. Also considered are the implications of each design for the interpretation of the results as well as threats to internalvalidity and ways to address them. The entry concludes with a summary of best practices to enhance the utility of quasi-experimental designs for studying behavior in the life span of human development

    Do early noun and verb production predict later verb and noun production? Theoretical implications

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    Many studies have addressed the question of the relative dominance of nouns over verbs in the productive vocabularies of children in the second year of life. Surprisingly, cross-class (noun-to-verb and verb-to-noun) relations between these two lexical categories have seldom been investigated. The present longitudinal study employed observational and parent-report data obtained from 30 mother-child dyads at 1;4, 1;8, and 2;0 to examine this issue. Both the Natural Partitions/Relational Relativity (NP/RR) hypothesis and the Emergentist Coalition Model (ECM) predict that having an initial repertoire of common nouns should facilitate the acquisition of novel verbs, whereas only the ECM suggests that children exploit the syntactic and semantic constraints of known verbs to infer the meaning of novel nouns. In line with the ECM, hierarchical regression analyses indicated that the percentages of nouns produced by children at 1;4 predicted later verbs at 1;8, whereas the percentages of verbs produced at 1;8 predicted later nouns at 2;

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods
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