bluuebunny/crossref_metadata_2025 huggingface dataset:
A Data‐Driven Approach for Repairing the Hydrological Catchment Signal Damage Due to Filtering of GRACE Products
Authors: Vishwakarma Bramha Dutt , Horwath Martin , Devaraju Balaji , Groh Andreas , Sneeuw Nico
Published: November 2017

One of the major sources of uncertainty in mass change estimates from level 02 grace products comes from the signal degradation due to filtering of noisy gravity field products. Filtering suppresses noise but also changes the signal via attenuation and leakage. Therefore, many methods have been devised to tackle the unavoidable signal loss due to filtering. However, most of these methods lack mathematical analysis that is essential for understanding the cause and effect of filtering. Furthermore, they use hydrological models to compute correction terms, such as leakage, bias, or scale factor, for repairing the damage due to filtering. Recently, a data‐driven method was proposed for improving the filtered grace products, which was shown to be superior to three widely used model‐based methods. However, the method works efficiently only for catchments above a minimum size. This limitation is due to the usage of a uniform layer approximation for deriving a scale factor, which is used to counter the attenuation of the catchment‐confined signal. In this contribution, we avoid this approximation, and therefore the usage of scale factor, which lifts the limitation and provides a better mathematical relation. The new data‐driven method is able to restore the signal loss due to filtering independent of the catchment size. We validate the method in a realistic grace‐type closed‐loop simulation environment and compare it with other popular approaches. We show that for 22 out of 32 catchments (small to large size and located in different climatic zones) the improved data‐driven method outperforms other methods.
Disability in a Global Context
Authors: Albrecht Gary L.
Published: November 2017

Disability is a condition that directly involves over 15% of the global population with reverberations throughout every nation and level of society. The World Bank, World Health Organization, and Gates Foundation emphasize that this population has serious social and economic effects on the stability and development of nations and well‐being of individuals touched by disability. This essay places disability in a global context and details the foundational work in the field. Cutting edge research combining biomedical advances, smartphone and computer technology, robotics, artificial intelligence and analysis of social networks and cultural contexts, disability activism and agency, and physical, social, political, and economic environments are examined. Looking to the future, the essay explores the consequences of global population growth, migration, environmental changes, and increased demand for services and technological innovation on the world's disabled population, their social networks, and nations. Lastly, the importance of exploring global disability in all areas of the world while being open to similarities and differences is emphasized.
Motivational Changes Across Adulthood: The Role of Goal Representations for Adult Development and Aging
Authors: Freund Alexandra M.
Published: November 2017

The importance of goals for understanding behavior and performance over time and across situations, for a sense of purpose and psychological well‐being, has been acknowledged in the areas of motivation and lifespan development for more than a quarter‐century (Baltes & Baltes, 1990). More recently, the field of motivated cognition has pointed to the role of the cognitive representation of goals for self‐regulation, affect, and goal achievement (Fujita & Carnevale, 2012). Owing to the decline in the perceived availability of goal‐relevant resources across adulthood, I argue that the representation of goals and their effects on behavior, performance, and well‐being changes across adulthood. More specifically, I propose that goal representations change dynamically as a response to—and help managing—the developmental gains and losses regarding (i) the orientation toward achieving gains, maintaining performance, or avoiding losses, and (ii) the focus on the means or the outcome of goal pursuit.
Cooperative Relationships
Authors: Hruschka Daniel J. , Silk Joan B.
Published: November 2017

Cooperative relationships arise from a history of mutually beneficial interactions between individuals, and they enable cooperation among a range of entities, including biological organisms, business firms, and nation‐states. As one of the simplest of emergent social forms, cooperative relationships can possess higher level properties (e.g., common expectations and rules of interaction, shared communication protocols) that are more than the sum of individual interactions. As such, cooperative relationships can become “things” in their own right, shaping how partners treat each other and how others treat partners within a relationship. Many open questions remain about how the emergent properties of cooperative relationships arise and how they foster future beneficial interactions while mitigating the risk of exploitation. Here, we frame these diverse findings and emerging questions in terms of the inputs and algorithms that partners use in forming models of each other and in guiding behaviors toward each other. We finish by outlining areas ripe for future exploration.
The Egg Freezing Revolution? Gender, Technology, and Fertility Preservation in the Twenty‐First Century
Authors: Inhorn Marcia C.
Published: November 2017

Egg freezing is the “newest” new reproductive technology, a form of flash‐freezing that allows human eggs to be successfully stored in egg banks. Touted as a “revolution in the way women age,” egg freezing is being heralded as a way for older career women to “rewind the biological clock.” This essay will examine the many factors in American women's lives—education, career, financial stability, relationship status, medical diagnosis and prognosis—that affect their egg freezing and disposition decisions. “Medical” egg freezing is being used by cancer patients, while “social” or “elective” egg freezing is being used by professional women in their late 30s and early 40s, both of whom face the threat of future infertility. Egg freezing among professional women represents a technological concession to ongoing gender inequalities in American society. These include employment constraints facing career women, the growing demographic surplus of college‐educated women who cannot find college‐educated male partners, and women's resultant delays in marriage and childbearing. Ultimately, egg freezing reveals a new and important interface of science and society—one with major implications for human reproduction, women's lives, and family formation in the twenty‐first century.
Skill Production Regimes and Immigrant Labor Market Integration
Authors: Kogan Irena
Published: November 2017

In recent years, Western countries have been experiencing a significant increase in both humanitarian and economic immigration. With the number of migrants, the challenges of integration have also surged. In consequence, host countries have invested a considerable amount of resources in comprehensive and effective immigrant integration policies. Various integration measures, such as foreign credential recognition or education and (re‐)training, have been implemented to help immigrants with their transition into the host country's labor market. The success of such policies, we argue, depends not only on their extent and coverage but also on whether they are compatible with other institutional characteristics of the host countries. This contribution hence asks to what extent host countries' immigrant integration policies aligned with these countries' skill production regimes channel immigrants into the labor market and consequently are responsible for the cross‐national differences in immigrants' economic integration. We expect that immigrants, particularly those with a less marketable status (e.g., refugees or asylum seekers), should have higher incentives to acquire host‐country‐specific education or to have their source country education recognized in countries that lay a stronger emphasis on highly specific vocational skills. They also should have higher labor market returns on their investments in countries with more vocationally oriented education systems (such as in Germany and Austria) as opposed to countries with more generally oriented education systems (such as Ireland and the United Kingdom).
The Economics of Conflict and Peace
Authors: Rohner Dominic
Published: November 2017

This essay takes stock of the existing literature in economics on the costs, consequences and causes of armed conflicts. The existing literature has put a particular focus, among others, on the impact of ethnic diversity, natural resource abundance and high poverty levels on the likelihood of conflict. Drawing on this, the current essay highlights several broad emerging trends in this literature. First of all, more and more papers use newly created, very fine‐grained data. Second, there is a trend towards linking more closely the empirical analysis to underlying theoretical frameworks. Third, there is a growing awareness of the importance of being policy relevant. Studying the impact of particular policies and institutions is likely to take a more central importance in this literature in the coming years.
Introduction to the Corporate Governance of Religion
Authors: Rost Katja
Published: November 2017

Stationed at the border between the past and the present, the corporate governance of religion is concerned with the governance mechanisms by which religious organizations are controlled and directed. Building on similarities between contemporary organizations and their predecessors in Roman Catholic monasticism, this essay illustrates that studying the past can be of enormous benefit. It allows us to see familiar problems in a new light: for example, bureaucratic rules—nowadays no longer linked to efficiency—that emerged in Catholic orders and enabled organizational learning, innovations, and survival in uncertain environments. The study of the past is also an appreciation for the kind of governance mechanisms that have staying power: Catholic orders can be viewed as pioneers of corporate governance and show what kind of governance is suitable to reduce agency problems. Finally, when abstract organizational theories are presented in a historical context, it makes them more palatable, more understandable, and more interesting: the theory of the optimal colocation of decision rights within the specific knowledge framework of organizations is supported in Catholic orders. They decentralize their local communities the higher the ratio of credence goods produced, and centralize their local communities the higher the ratio of search/experience goods produced.
The Role of Death Denial in Culture and Consciousness
Authors: Solomon Sheldon
Published: November 2017

Independent lines of theoretical inquiry in evolutionary psychology and existential psychodynamic psychology propose that the awareness of the inevitability of one's death would undermine the viability of consciousness as an adaptive form mental organization in the absence of death‐denying cultural and psychological affectations. In accord with this view, empirical research derived from terror management theory demonstrates that intimations of mortality have a pervasive effect on a wide range of human beliefs and behaviors.
Early Childhood Education and Care Services and Child Development: Economic Perspectives for Universal Approaches
Authors: Spiess C. Katharina
Published: November 2017

This essay analyses universal early childhood education and care (ECEC) services from an economic perspective focusing on universal ECEC approaches. First, it examines the effectiveness of ECEC expansions, reviewing research using quasi‐experimental approaches. It then discusses the possible mechanisms underlying the measured effects. These are related to both direct effects from ECEC services on children and indirect ones occurring via maternal employment and well‐being. When ECEC‐positive effects are detected, they mostly pertain to children from lower socioeconomic backgrounds. This raises the question as to whether this group of children is reached by universal ECEC services. The second part of the essay focuses on this issue, describing differences in ECEC attendance by socioeconomic background, distinguishing between different age groups and different aspects of ECEC attendance. The challenges for future research are summarized at the end.
Macroeconomic Effects on Mortality: Issues, Controversies, and Directions for Research
Authors: Granados José A. Tapia
Published: November 2017

This essay examines the development of ideas on the macroeconomic effects on mortality. It surveys some nineteenth century views, the early twentieth century contributions of Ogburn and Thomas, the 1970s–1980s debates of Brenner and Eyer, and the modern views, contributions, and controversies involving Ruhm and other authors who have tried to demonstrate the empirical support—or the lack of it—for the contentious hypothesis of the procyclical oscillation of mortality. That is the pattern, now clearly established for many, but unproved for more than a few skeptics, that once long‐term trends are taken away, mortality oscillates with the business cycle, rising in expansions and declining in recessions. Potential sources of discrepancies, hypothesized or proven mechanisms for procyclical mortality, and related policy issues are discussed, and the essay concludes by suggesting five questions that future research should aim to answer.

To the memory of Joe Eyer, 1944–2017
Cultural Psychology, Socialization, and Individual Development in Changing Contexts
Authors: Trommsdorff Gisela
Published: November 2017

This essay discusses two major emerging trends in the study of culture and psychology. One trend can be observed in the reconciliation of cross‐cultural and culture‐indigenous approaches due to conceptualizing culture in a value‐ and norm‐oriented framework of cultural meaning and cultural minds. A second trend is based on questions of culture learning and socialization, reconciling the nature–nurture debate. Developmental studies integrating biological and socialization conditions in cultural contexts are complemented by selected studies on culture‐specificities of self‐regulation, prosocial behavior, caretaker's implicit theories on parenting, and intergenerational relations. The meaning‐making function of socialization is seen as a major process in culture learning and the development of cultural mindsets. I conclude with questions regarding socioeconomic, demographic, and cultural changes, suggesting a major research goal for an emerging science of cultural psychology: to provide a scientific basis for better understanding culture‐psychological conditions and consequences of fundamental ongoing changes related to cultural diversity and to accelerating intercultural connections.
Complex Religion: Toward a Better Understanding of the Ways in which Religion Intersects with Inequality
Authors: Wilde Melissa J. , Tevington Patricia
Published: November 2017

Sociologists have long known that religion is deeply interconnected with race, class, and ethnicity in the United States. However, modern sociologists typically study religion as if it is independent from other social structures. Profound class differences remain between American religious groups. Jews, Mainline Protestants and new immigrant groups such as Hindus are at the top of the socioeconomic ladder. Conservative Protestants, both Black and White remain at the bottom. We therefore argue that religion is not independent of class and race and should almost always be examined in interaction with these and other social structures. We call this, theoretical approach “complex religion.”
Evidence of Causation—The Contribution of Life Course Research, Part I: Dominant Models of Causal Inference and Their Limitations in Life Course Research
Authors: Blossfeld Hans‐Peter
Published: November 2017

Life course research has been increasingly criticized for relying only on observational data where processes by which subjects select themselves (or are selected) into the states of a causal variable are not under the control of the researcher. The primary objectives of this essay,
the first in a two‐part set
, are to discuss two dominant models of causal inference and to identify the uses and limitations of randomized control trials (RCTs) and quasi‐experimental designs for answering life course questions.
Evidence of Causation—The Contribution of Life Course Research, PartII: Causation as Generative Process
Authors: Blossfeld Hans‐Peter
Published: November 2017

This is thesecond part in a pair of essayson causal inference in life course research. The first part presented the dominant models of causal inference and their limitations in life course research. This essay develops the idea of “causation as generative process,” offering a quite promising model for inferences in life course research.
Amos (Software)
Authors: Barnidge Matthew , De Zúñiga Homero Gil
Published: November 2017

This entry seeks to highlight some of the basics and functional characteristics of the Amos (Analysis of Moment Structures) statistical module. First, it explores the software's primary features and available tests for covariance structure models. Then, it elaborates on command program and other advanced features. Finally, it suggests further reading on the topic.
Analysis of Cognitive Communication Scripts
Authors: Hart Tabitha
Published: November 2017

Cognitive scripts are mental models that tell us how to “do” routine and nonroutine activities; they are invaluable sociocultural resources that we utilize to successfully and smoothly play our parts in our social worlds. We learn cognitive scripts through the process of socialization and subsequently draw on them to anticipate, decode, and strategically engage in social activity.
Card Pile Sort (Coding)
Authors: DeSantis Alan D.
Published: November 2017

Card‐pile sorting is a traditional method of managing qualitative data on paper (3 × 5 inches or 4 × 6 inches) index cards. Many researchers find it advantageous to be able to physically touch and manipulate these analog cards when sorting, coding, and organizing their qualitative datasets.
Case Study Research
Authors: Simmons Nathaniel
Published: November 2017

Case study research is a versatile, highly flexible, and adaptive approach to qualitative research. Focusing upon single or multifaceted contexts and phenomena, case study research proffers great potential for theory construction. Although misunderstandings of case studies exist, case studies offer several benefits such as providing in‐depth descriptions of communicative phenomena and sites for theory testing and construction.
Code List/Codebook
Authors: Hampsten Katherine
Published: November 2017

The codebook/code list provides a compilation of codes used to organize and analyze research data. It provides a detailed record of the categories, code names or labels, definitions, and examples of each unit of data. Crafting a well‐designed codebook/code list is a reflective and iterative process for the research team.
Common Method Bias
Authors: Vishwanath Arun
Published: November 2017

Common method bias is the spurious correlation between two or more variables stemming from the shared method used to measure them. Communication scholars seldom acknowledge this issue as a possible contaminant of their results. The current entry presents an overview of common method bias along with the major approaches for detecting and preventing method bias in communication research.
Community‐Based Participatory Focus Groups
Authors: Tapp Hazel , De Hernandez Brisa Urquieta , Smith Heather
Published: November 2017

Within community‐based participatory research, focus groups are a commonly used qualitative research tool. Well‐designed and effectively facilitated focus groups generate rich data using participants' insights to “trigger” the sharing of others' personal experiences and perspectives in a way that teases out nuances and tensions of complex topics and subjects.
Confoundation Check
Authors: Hofer Matthias
Published: November 2017

A confounding variable is a variable that is associated with both the independent and the dependent variable and thus obscures or accentuates the relationship between the two. In experimental research, researchers are faced with a confoundation if the experimental manipulation(s) did inadvertently affect other variables. Therefore, in order to be able to draw valid causal conclusions researchers have to conduct (a) confoundation check(s). Crucial to the performance of such tests is their ordering and timing.
Constant Comparison
Authors: Smulowitz Stacy
Published: November 2017

A common method of data analysis is constant comparison where qualitative researchers look for similarities and differences in the data. Those data that are similar are grouped together under a key word or category. As the researcher reviews data, each new piece of data is compared and contrasted to previous data and sorted into the most relevant category. Once all the data have been reviewed the researcher may find that some categories can be collapsed. Finally, the researcher will look across the categories for patterns or themes to the data.
Conversation Analysis
Authors: Stefano Antonio Di
Published: November 2017

This entry sets out to reconstruct the intrinsic properties of conversation analysis by focusing on its methodological, empirical, and theoretical foundations.CAis aimed at unveiling social and linguistic instances that make any talk in interaction a situated conversation imbued with intersubjective meanings. The entry illustrates research implications strictly related to conversation analysis in the broader field of communication study.
Document Analysis
Authors: Smulowitz Stacy
Published: November 2017

The inclusion of documents in a qualitative research study can provide additional rich data. There is an abundance of document types that the qualitative researcher can consider for their study and multiple types of data can be used in the same study. Through analyzing documents, the qualitative researcher can evaluate their meaning, along with other types of data, to further support the research findings. Common types of data analysis for qualitative studies include content analysis and constant comparison.
Dramatistic (Burkean) Criticism
Authors: Westerfelhaus Robert
Published: November 2017

This entry provides an overview of the main contributions of Kenneth Burke to the field of rhetorical theory. The concepts covered include the pentad and its component parts; the guilt‐redemption cycle, with its sources and its remedies; identification and terministic screens.
Ethnography/Ethnographic Methods
Authors: Chawla Devika , Jones Rebecca Mercado
Published: November 2017

This entry provides an extended description of the meaning and forms of ethnography. It begins with a survey of definitions of the wordethnographyand how it has been disparately defined across fields. Following this, a brief history of the ethnographic enterprise is charted from the late nineteenth century to the present day. Subsequently, we discuss ethnographic methods by identifying, fieldwork, participant observation, field notes, and interviewing as some of the key tools used in ethnographic research. We conclude with a discussion of five modes of ethnographic research and writing: interpretive ethnography; critical ethnography; performance ethnography; feminist ethnography; and autoethnography.
Evocative Writing
Authors: Poulos Christopher N.
Published: November 2017

Evocative writing is a way of constructing research texts that conjure, arouse, or elicit vivid images, deep meanings, and intense emotions. Here evocative writing is explored via an intensive search through these layers of imagery, meaning, and emotion.
Experiment, Laboratory
Authors: Leshner Glenn
Published: November 2017

This entry discusses the logic and basics of controlled experiments, including fundamental issues of creating experimental conditions, random assignment, and eliminating confounds. Important considerations in experimental research are reviewed, including operationalizing independent variables, sample size and composition, and manipulations checks. A few important historical developments of experiments and research laboratories in communication research are presented, followed by a brief discussion about different types of experimental research in the communication literature. Lastly, the entry covers some limitations of experimental research and laboratory experiments in particular.
Experimental Design
Authors: Bellman Steven
Published: November 2017

Well‐designed experiments provide the best possible data for showing that one variable
causes
another variable. Causative explanations are the building blocks of theory in communication research and science generally. Experimental design is what researchers do before carrying out an experiment. This entry describes the differences between the two basic kinds of experimental design, between‐groups designs and within‐participants designs. It provides guidelines for choosing between these two types of designs, or for using both in a mixed design. To make a strong case for causation, a well‐designed experiment has to rule out alternative plausible explanations for the experiment's results that threaten its internal or external validity. Finally, this entry discusses how new methods allow communication researchers to carry out experiments with high levels of control outside the unnatural environment of a lab. These discussions are illustrated with examples of real‐life experiments conducted in a busy media research lab.
Factor Analysis, Exploratory
Authors: Morrison John T.
Published: November 2017

Exploratory factor analysis is an inductive, data‐driven approach to a factor analysis used when no clear expectations are proposed regarding outcomes. An EFA is not a single technique; it represents a comprehensive suite of multivariate statistical operations that attempt to condense a larger number of quantifiable variables into a smaller number of conjectural variables called factors. Purposes for an EFA include the discovery, substantiation, measurement, and explanation of latent variables, the identification of reliable observable variables related to those latent variables, and optionally, the generation of case‐level factor scores. Common uses for an EFA in communication research include the creation and substantiation of attitude measurements, social scales, item design and assessment, measurements of communication abilities, and the dimensionalization of latent communication constructs. Social and communication research presents additional methodological and interpretive complexity for an EFA, because construct conceptualizations and methods are inconsistent, considerable error exists, and because communication factors are often strongly related. Misunderstanding and underreporting of process decisions in communication studies is common.
Field Sites
Authors: Simmons Nathaniel
Published: November 2017

Qualitative field sites refer to specific geographic, social, and/or virtual locations or contexts for research. Field sites are bound and influenced by time and space. In the era of globalization, field sites reveal themselves to be contested, cultural, hybridized spaces, which require attention to glocal meanings for one's elected site.
Hypotheses, Types Of
Authors: Naderer Brigitte
Published: November 2017

In social science, a hypothesis describes an empirically testable proposition. This entry differentiates three main types of hypotheses: First, a
causal hypothesi
s that is either stated in terms of “if – then” or “the more – the more (less)” predictions; second, a
trend‐
or
development hypothesis
that assumes a change over time; and third, an
attribute association
which states a connection of two variables that cannot be causally interpreted.
In‐Depth Interviews
Authors: Faulkner Sandra L. , Trotter Stormy P.
Published: November 2017

In‐depth interviews represent a subset of interviewing techniques characterized by the collection of highly detailed and rich information, flexible interview protocols, and open‐ended questions. They range in form from the use of highly structured interview and semistructured interview guides with preset and follow‐up questions about a specific topic to informal and conversational interviews used for clarification and filling in missing information.
Interactive Content, Analysis Of
Authors: Schmierbach Mike
Published: November 2017

Interactive media offer users power over media, but in the process complicate effective content analysis. This entry addresses the most prominent difficulties in sampling, unitizing, coding, and analyzing interactive content, offering examples of how these problems occur and solutions or alternatives where relevant. Scholars studying video games, social networks, online news, and many other emerging media can improve the quality of their content analysis data by carefully considering these points when designing and executing a study.
Interactive Focus Groups
Authors: Vangelis Linda
Published: November 2017

Interactive focus groups, as an interpretive method of research, may be used to obtain a rich, deep understanding of participants' experiences when conducting focus group interviews. This method includes participants as co‐collaborators with the researcher in the research process. The researcher becomes a full participant in the interview process, sharing stories, opinions, reflections, and observations with the group members, and empowering participants to share control and direction of the interview process with the researcher.
Intersubjectivity
Authors: Bae Soyoung
Published: November 2017

Intersubjectivity can be viewed as the middle ground between objectivity and subjectivity because it contains characteristics of both epistemological stances. Intersubjectivity is focused on the belief that research is neither purely objective nor purely subjective in nature. In this entry intersubjectivity is described as agreement among scientists occurring via communication and the sharing of meanings regarding their research objects and research contexts. The assumptions on symbolic interactionism are provided to help better understand intersubjectivity based on how the meanings attached to objects are shared among people through interactions. Finally, two classifications of intersubjectivity are introduced. Three commonalities from these classifications are intersubjectivity by regimentation/standardization, intersubjectivity by explicitness/explication, and dialogical intersubjectivity/members check.
Latent Class Analysis
Authors: Karnowski Veronika
Published: November 2017

Latent class analysis is a statistical procedure to identify underlying and unobservable categorical latent variables based on categorical observed indicators. By attributing cases to the value of the categorical latent variable it most probably belongs to, latent class analysis can be used for clustering. Latent class analysis does have a series of advantages compared to conventional clustering techniques: (i) The choice of a cluster criterion is less arbitrary due to the underlying statistical model. (ii) Being a model‐based approach it provides several rigorous statistical tests to assess model fit. (iii) It also provides formal criteria to make decisions about the appropriate number of clusters. (iv) Latent class clustering can include observed variables of different scaling and measurement levels. (v) The probabilistic nature of cluster membership in latent class cluster analysis leads to less biased estimations of class‐specific means, as each case only contributes to this mean weighted by its class membership probability. (vi) The misclassification error can be calculated and reported. Despite these advantages latent class analysis has only scarcely been used in communication research thus far, a fact that is likely to change with the ever‐increasing uptake of comprehensive solutions for data analysis (e.g., the software environment R).
Latent Growth Curve Modeling
Authors: Schemer Christian , Geiss Stefan
Published: November 2017

Latent growth curve models (LGCM) are a versatile tool to model change in individual units over time. The most common application in communication research is the analysis of panel data. Univariate LGCMs describe the change of a single observed or latent variable over time. Multivariate LGCMs include predictors of growth processes, consequences of growth processes, and/or parallel growth curves, which model the influences between multiple growth processes. Latent growth curve models may also incorporate autoregressive terms, and growth mixture models distinguish different growth processes in different latent classes. The entry introduces these different kinds of models and demonstrates their application using publicly available sample data.
Latent Mean (Comparison)
Authors: Müller Philipp , Schäfer Svenja
Published: November 2017

The term latent mean describes the mean values of latent constructs within the structural equation modeling (SEM) framework. Usually, SEM is based merely on the covariance structure of the data. However, it is possible to add a mean structure to the model. This makes it possible to compare the mean values of latent factors within different populations or at different points in time. The entry explains the advantages of using latent instead of observed means and introduces structured means modeling (SMM) as an established technique for latent mean comparison. We also introduce an alternative approach to latent mean comparison: Multiple‐Indicator Multiple‐Cause (MIMIC) models. Finally, we discuss how and why comparative and experimental communication research should make use of latent mean comparison.
Longitudinal Data Analysis, Panel Data Analysis
Authors: Grill Christiane
Published: November 2017

Longitudinal or panel data analysis refers to the statistical analysis of pooled data which consists of a cross‐section of units (e.g., countries, firms, households, individuals) for which there exist repeated observations over time. Many of the longitudinal data applications that appear in the literature are based on linear model theory. The most prominent linear panel data models are the fixed‐effects model, and the random‐effects model, both of which are applied to model the level of the dependent variable. As to the most prominent approaches in order to model the change of the dependent variable, the lagged dependent variable approach, and the change score method are most frequently utilized. Although panel data offer many advantages to study causal propositions, the power of the analysis largely depends on the assumptions inherent in the statistical models.
Mean Centering
Authors: Hofer Matthias
Published: November 2017

Mean centering is an additive transformation of a continuous variable. It is often used in moderated multiple regression models, in regression models with polynomial terms, in moderated structural equation models, or in multilevel models. Mean centering has been offered as a remedy for problems of collinearity in moderated multiple regression models or in polynomial regression models. But, mean centering does not reduce essential collinearity due to substantial relationships between variables. However, for the sake of interpretability of results it is recommended that researchers center predictor variables when their variables do not have meaningful zero points. Mean centering in multilevel models is more complex, as two types of mean centering are available.
Measurement of Media Exposure
Authors: Nagler Rebekah H.
Published: November 2017

How to measure media exposure is one of the most central—and most challenging—questions in communication research, particularly the media effects paradigm. For there to be media effects, there must first be media exposure, defined as the extent to which individuals encounter specific media messages or content. Remarkably, despite media exposure's centrality to the study of effects, there has been little scholarly consensus on how to measure it. This entry begins by reviewing traditional approaches to measurement, describing the major classes of exposure measures and drawing on examples from health communication, political communication, and other media effects domains. This historical approach to measurement is contrasted with more recent developments, including efforts to provide reliability and validity evidence for novel measures. The entry concludes by considering future questions that could be addressed by media effects scholars interested in advancing measurement of media exposure.
Memory, Measurement Of
Authors: Yegiyan Narine
Published: November 2017

The entry provides an overview of different measures of memory employed in communication research. Recognition, cued recall, free recall, and serial recall are explored, both in terms of the cognitive subprocesses they are thought to index and in terms of specific ways in which researchers can operationalize these measures in their own work.
Messy Data, Analysis Of
Authors: Shahin Saif
Published: November 2017

Raw data collected through surveys, experiments, coding of textual artifacts, or other quantitative means may not meet the assumptions upon which statistical analyses rely. The presence of univariate or multivariate outliers, skewness or kurtosis in a distribution, and heteroscedasticity or multicollinearity among variables may compromise data analysis. Scholars have devised a variety of techniques to discern and address such problems.
Mplus
Authors: Mangold Frank
Published: November 2017

This entry introduces the state‐of‐the‐art latent variable modeling program Mplus. It gives an overview of the wide array of powerful modeling features, estimators, and algorithms that Mplus integrates into a powerful general framework. The practical use of Mplus and its benefits are also covered.
Narrative Analysis/Inquiry
Authors: Odette Wright Kallia
Published: November 2017

Narrative analysis/narrative inquiry is the process of analyzing stories gathered from various sources to gain insight into the storied nature of human experience. An interpretive approach, narrative analysis focuses on the subjective interpretation of human conditions and experiences by the participant as well as the researcher and uses various conceptual frameworks to analyze both. Stories are valuable for analysis as people often reveal their world, their identity, points of view, cultural norms, standpoints and beliefs, thoughts, and emotions about the social world through them. This entry contains a summary of the key concepts of narrative analysis, the approaches to using narrative inquiry as a qualitative communication research method. The strengths and limitations of narrative inquiry are also offered, along with suggestions for future research.
Online Ethnography
Authors: Hart Tabitha
Published: November 2017

Conducting an online ethnography involves applying a traditional ethnographic approach to virtual and/or online settings. It requires a sustained period of immersion in the virtual field site, during which time the online ethnographer engages in observation and/or participant observation in the virtual community under study. Online ethnographers produce reports describing and analyzing the sociocultural lifeworlds that exist in virtual and technology‐mediated spaces. While online ethnography is not radically different to traditional ethnography, online ethnographers do face unique methodological, philosophical, and ethical challenges as they explore online scenes, communities, and worlds.
Path Analysis
Authors: Valenzuela Sebastián , Bachmann Ingrid
Published: November 2017

Path analysis is a statistical technique for examining and testing relationships among a set of observed variables. Path analysis allows the study of multiple direct and indirect relationships between variables simultaneously. It is now regarded as one type of the more general statistical technique known as structural equation modeling. To facilitate interpretation, the estimated relationships in a path analysis are usually presented in the form of a path diagram, with boxes representing variables and arrows representing paths of relationships. With path analysis, researchers can determine if a proposed model is consistent with the data throughout.
Performative Social Science
Authors: Jones Kip
Published: November 2017

Performative Social Science (PSS) is positioned within the current era of cross‐pollination from discipline to discipline. Practitioners from the arts and humanities look to the social sciences for fresh frameworks, whilst social science practitioners explore the arts for potential new tools for enquiry and dissemination. PSS is defined and the similarities and differences between PSS and Arts‐based Research (ABR) are delineated. The history of PSS is then outlined and its development, particularly at the Centre for Qualitative Research at Bournemouth University in the United Kingdom, is reviewed. Relational aesthetics is then described in depth as the theoretical basis and grounding of PSS. Relational aesthetics offers a theoretical ground for the complexities of connections across seemingly disparate disciplines, such as the arts and social sciences, and for further exploration of the synergies between both disciplines as well as communities beyond the academy. An example of a large, three‐year nationally funded project, culminating with the production of an award‐winning short biopic,
Rufus Stone
, is outlined as a prime example of a multimethod approach to social science research which includes tools from the arts in its progress and outputs. The entry concludes with goals and aspirations for PSS in the future.
p
‐Hacking
Authors: Arendt Florian
Published: November 2017

p
‐Hacking describes a practice where researchers analyze their data in a multiple of different ways to get the desired result (a significant effect). This practice is problematic for scientific progress, because it contributes to incorrect rejections of null hypotheses.
p
‐Hacking can include a number of relevant decisions in the data analysis process such as what statistical tests to perform or what cases or conditions to exclude.
Positivism
Authors: Shapiro Tammy
Published: November 2017

The term “positivism” is used often in the social sciences to characterize research or theory as, variously, quantitative, foundationalist, realist, empiricist, or as excluding interpretative and qualitative methods. However, positivism over the past two centuries has included diverse epistemological stances and methodological practices. This article broadly outlines positivism's developmental trajectory from Comte's naïve empiricism and Enlightenment project to the neopositivism of the logical empiricists associated with the Vienna Circle to the postpositivism of 1950s and 1960s philosophy of science. The various approaches within the positivist framework have fundamentally shaped contemporary philosophy of the social sciences.
Publication Bias
Authors: Marquart Franziska
Published: November 2017

Publication bias refers to the tendency of research results to be selectively published depending on their nature and direction, with positive and significant findings that are in line with theory being more likely to get published. This bias has been detected at the level of authors, reviewers, and journal editors alike.
Q‐Sort Methodology
Authors: Lee Joomi
Published: November 2017

This entry introduces the principles and procedures of Q‐sort methodology which aims to examine individuals' differing subjectivity (i.e., viewpoints, attitudes, beliefs) toward a specific context or object. It describes Q‐sort methodology as a systematic research method that is designed to incorporate the qualitative study of human subjectivity to the quantitative research tradition.
Qualitative Analysis Software
Authors: Hart Tabitha , Achterman Peg
Published: November 2017

Qualitative data analysis is a rigorous, complex, iterative, nonlinear, and intellectually demanding method of discerning and describing emergent patterns in rich and nonuniform qualitative datasets. This entry summarizes the key tasks that qualitative data analysis (QDA) software programs can be used for, including systematizing and categorizing electronic datasets, producing reports, and engaging in collaborative research projects. It also describes the key criteria that researchers must consider before selecting a QDA program. It concludes with a brief overview of seven popular QDA programs: ATLAS.ti, Dedoose, The Ethnograph, MAXQDA, NVivo (formerly NUD*IST), TAMS Analyzer, and Transana.
Qualitative Research Question
Authors: Martin Kelly Norris
Published: November 2017

This entry discusses the various purposes of the qualitative research question, the typical phrasing of the question, and categories of questions.
Queer Studies
Authors: Adams Tony E. , Jones Stacy Holman
Published: November 2017

This entry provides an overview and history of queer studies, particularly within the communication discipline, as well as outline characteristics of queer communication projects.
R
(Software)
Authors: Breuer Johannes
Published: November 2017

R is a programming language and a freely available open‐source software environment for statistical analyses and graphics (see
http://www.r‐project.org/
). Besides being free and open‐source, R has recently seen a surge in popularity mainly for its graphical capabilities for producing publication‐ready tables and figures, and its functionalities for advanced multivariate analyses, such as structural equation and multilevel modeling. Graphical user interfaces (GUIs), such as
RStudio
(
http://www.rstudio.com/
), can facilitate the use of R for users who are more familiar with statistical packages like
SPSS
,
SAS
, or
Stata
.
Reactivity
Authors: Schlütz Daniela M.
Published: November 2017

Reactivity is an unwanted effect of empirical research restricting validity. The term designates the fact that each measurement process alters the social reality that it should merely observe. In practice, participants are sensitized by the research process, which influences their reactions (answers and/or behaviors) and causes systematic errors. Examples of response biases are the social desirability bias, non‐opinions, satisficing, and acquiescence.
Regression Analysis, Nonlinear
Authors: Fu Hanlong
Published: November 2017

Nonlinearity is common in communication research. When nonlinearity is not properly addressed, conclusions based on linear assumptions could be unreliable. This entry discusses the definition of nonlinearity, forms of nonlinearity, and ways to address different forms of nonlinearity using statistical models that are common in communication research.
Research Method Selection
Authors: Schulz Anne
Published: November 2017

This entry introduces different criteria that may guide the selection of research methods within communication science. In general this selection process can be driven by the respective research question and hypothesis, and by ethical, practical, or policy considerations, as well as by specific research traditions.
Response Sets
Authors: Applequist Janelle
Published: November 2017

Most often, response set refers to a person framing their responses or statements in a way that is consistent with social desirability. Respondents engage in social desirability bias because they would prefer to look favorable as opposed to unfavorable to the researcher or society. Two ways in which respondents perpetuate social desirability bias is through the overreporting of their good behavior and the underreporting of their bad behavior. Valid and reliable research studies rely upon their measurement. Because self‐report surveys and questionnaires are such popular measures for participant views and beliefs, it is necessary that researchers consider the framing of their questions alongside ways that can help to garner truthful, accurate responses.