This groundbreaking edited book, The Routledge Handbook for Advancing Integration in Mixed Methods Research, presents an array of different integration ideas, with contributions from scholars across ...the globe. This handbook represents the first major volume that comprehensively discusses this topic of integration. Perhaps the most fundamental and longstanding question in mixed methods research is: How does one best integrate disparate forms of information to produce the best form of inquiry? Each of the 34 seminal chapters in this handbook accelerates the discussion of integration across a broad range of disciplines, including education, arts-based analyses, and work in the Global South, as well as special topics such as psychometrics and media research. Many of the chapters present new topics that have never been written about before, and all chapters offer cutting-edge approaches to integration. They also offer different perspectives of integration – leading the introductory chapter to offer a new and comprehensive definition for integration, as follows: "referring to the optimal mixing, combining, blending, amalgamating, incorporating, joining, linking, merging, consolidating, or unifying of research approaches, methodologies, philosophies, methods, techniques, concepts, language, modes, disciplines, fields, and/or teams within a single study." The concluding chapter offers a meta-framework that accounts for this definition and is designed to help scholars think more about integration in a way that represents a continuous, dynamic, iterative, interactive, synergistic, and holistic meaning-making process. This handbook will be an essential reference work for all scholars and practitioners using or seeking to use mixed methods in their research.
Reflecting on common empirical concerns in quantitative entrepreneurship research, recent calls for improved rigor and reproducibility in social science research, and recent methodological ...developments, we discuss new opportunities for further enhancing rigor in quantitative entrepreneurship research. In addition to highlighting common key concerns of editors and reviewers, we review recent methodological guidelines in the social sciences that offer more in-depth discussions of particular empirical issues and approaches. We conclude by offering a set of best practice recommendations for further enhancing rigor in quantitative entrepreneurship research.
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BFBNIB, FZAB, GIS, IJS, KILJ, NUK, OILJ, SAZU, SBCE, SBMB, UKNU, UL, UM, UPUK
Nonnormality of univariate data has been extensively examined previously (Blanca et al.,
Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 9
(2), 78–84,
2013
; ...Miceeri,
Psychological Bulletin, 105
(1), 156,
1989
). However, less is known of the potential nonnormality of multivariate data although multivariate analysis is commonly used in psychological and educational research. Using univariate and multivariate skewness and kurtosis as measures of nonnormality, this study examined 1,567 univariate distriubtions and 254 multivariate distributions collected from authors of articles published in Psychological Science and the American Education Research Journal. We found that 74 % of univariate distributions and 68 % multivariate distributions deviated from normal distributions. In a simulation study using typical values of skewness and kurtosis that we collected, we found that the resulting type I error rates were 17 % in a
t
-test and 30 % in a factor analysis under some conditions. Hence, we argue that it is time to routinely report skewness and kurtosis along with other summary statistics such as means and variances. To facilitate future report of skewness and kurtosis, we provide a tutorial on how to compute univariate and multivariate skewness and kurtosis by SAS, SPSS, R and a newly developed Web application.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Abstract
Nowadays, registered hate crimes are on the rise in many Western societies. What explains temporal variation in the incidence of hate crimes? Combining insights from the grievance model and ...the opportunity model, we study the role of three types of contextual factors: security (terrorism), media (news about terrorism and immigration), and political factors (speech by anti-immigration actors, hate speech prosecution, and high-profile anti-immigration victories). We apply time-series analysis to our original dataset of registered hate crimes in the Netherlands, 2015–2017 (N = 7,219). Findings indicate that terrorist attacks, (both print and online) news on refugees, immigration, and terrorism boost nonviolent hate crime. Similarly, news of the hate speech prosecution of Freedom Party leader Geert Wilders increases nonviolent crime as well. Tentative evidence points to a contagion effect of speech by anti-immigration actors. With regard to violent hate crime, only terrorist attacks had an effect. This effect was modest and only found in one of our models. Hence, the grievance and the opportunities model each partially explain nonviolent hate crime, although the security and media context seem most influential. Our findings help to identify the contextual factors contributing to a climate for hate and suggest that perceived threats play a key role.
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DOBA, IZUM, KILJ, NUK, ODKLJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Survey experiments are ubiquitous in social science. A frequent critique is that positive results in these studies stem from experimenter demand effects (EDEs)—bias that occurs when participants ...infer the purpose of an experiment and respond so as to help confirm a researcher’s hypothesis. We argue that online survey experiments have several features that make them robust to EDEs, and test for their presence in studies that involve over 12,000 participants and replicate five experimental designs touching on all empirical political science subfields. We randomly assign participants information about experimenter intent and show that providing this information does not alter the treatment effects in these experiments. Even financial incentives to respond in line with researcher expectations fail to consistently induce demand effects. Research participants exhibit a limited ability to adjust their behavior to align with researcher expectations, a finding with important implications for the design and interpretation of survey experiments.
Does X affect Y? Answering this question is particularly difficult if reverse causality is looming. Many social scientists turn to panel data to address such questions of causal ordering. Yet even in ...longitudinal analyses, reverse causality threatens causal inference based on conventional panel models. Whereas the methodological literature has suggested various alternative solutions, these approaches face many criticisms, chief among them to be sensitive to the correct specification of temporal lags. Applied researchers are thus left with little guidance. Seeking to provide such guidance, we compare how different panel models perform under a range of different conditions. Our Monte Carlo simulations reveal that unlike conventional panel models, a cross-lagged panel model with fixed effects not only offers protection against bias arising from reverse causality under a wide range of conditions but also helps to circumvent the problem of misspecified temporal lags.
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Indirect reciprocity is the most elaborate and cognitively demanding of all known cooperation mechanisms, and is the most specifically human because it involves reputation and status. By helping ...someone, individuals may increase their reputation, which may change the predisposition of others to help them in future. The revision of an individual's reputation depends on the social norms that establish what characterizes a good or bad action and thus provide a basis for morality. Norms based on indirect reciprocity are often sufficiently complex that an individual's ability to follow subjective rules becomes important, even in models that disregard the past reputations of individuals, and reduce reputations to either 'good' or 'bad' and actions to binary decisions. Here we include past reputations in such a model and identify the key pattern in the associated norms that promotes cooperation. Of the norms that comply with this pattern, the one that leads to maximal cooperation (greater than 90 per cent) with minimum complexity does not discriminate on the basis of past reputation; the relative performance of this norm is particularly evident when we consider a 'complexity cost' in the decision process. This combination of high cooperation and low complexity suggests that simple moral principles can elicit cooperation even in complex environments.
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Determining whether people in certain countries score differently in measurements of interest or whether concepts relate differently to each other across nations can indisputably assist in testing ...theories and advancing our sociological knowledge. However, meaningful comparisons of means or relationships between constructs within and across nations require equivalent measurements of these constructs. This is especially true for subjective attributes such as values, attitudes, opinions, or behavior. In this review, we first discuss the concept of cross-group measurement equivalence, look at possible sources of nonequivalence, and suggest ways to prevent it. Next, we examine the social science methodological literature for ways to empirically test for measurement equivalence. Finally, we consider what may be done when equivalence is not supported by the data and conclude with a review of recent developments that offer exciting directions and solutions for future research in cross-national measurement equivalence assessment.
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BFBNIB, CMK, INZLJ, NMLJ, NUK, ODKLJ, PNG, SAZU, UL, UM, UPUK, ZRSKP
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