Cluster analysis in community research: Epistemology and practice

Cluster analysis refers to a family of methods for identifying cases with distinctive characteristics in heterogeneous samples and combining them into homogeneous groups. This approach provides a great deal of information about the types of cases and the distributions of variables in a sample. This paper considers cluster analysis as a quantitative complement to the traditional linear statistics that often characterize community psychology research. Cluster analysis emphasizes diversity rather than central tendency. This makes it a valuable tool for a wide range of familiar problems in community research. A number of these applications are considered here, including the assessment of change over time, network composition, network density, person-setting relationships, and community diversity. A User's Guide section is included, which outlines the major decisions involved in a basic cluster analyses. Despite difficulties associated with the identification of optimal cluster solutions, carefully planned, theoretically informed application of cluster analysis has much to offer community researchers. Editor's note: Dr. Edward Seidman served as action editor for this article while serving as Associate Editor for Methodology.     

Cares,Identification, and Agency Reductionism

Reductionists about agency maintain that an agent's causing something is reducible to states and events involving the agent causing something. Some worry that reductionism cannot accommodate robust forms of agency, such as self‐determination. One reductionist answer to this worry, which I call ‘identification reductionism,’ contends that self‐governing agents are identified with certain attitudes, and so these attitudes causing a decision count as the agent's self‐determining the decision. I argue that a prominent species of identification reductionism developed by Harry Frankfurt, Agnieszka Jaworska, Jeffrey Seidman, and David Shoemaker – according to which an agent is identified with his (deepest) cares – is inadequate.     

Narrative vignettes and online enquiry in researching therapist accounts of practice with children in schools: An analysis of the methodology

Aims: This article reviews a research methodology that uses an Internet mediated qualitative, narrative approach to provide in‐depth analysis of vignettes. The research sought to investigate the ways in which dramatherapists, based in different countries, understood the nature of therapeutic change in their work with children. Method: The article describes a qualitative approach to the generation of data by a combination of therapist‐authored vignettes, live, synchronous Internet mediated communication (aMSN Messenger) and email. Participants kept a diary of their response to the research and the article draws on this data within its analysis of the methodology. Findings: Samples of the data are used to analyse how such innovative, online methodology can develop effective access and relationships with geographically dispersed participants and as an effective way of investigating therapist practitioners' understanding of their practice.     

Analysis of Variance of Multiply Imputed Data

As a procedure for handling missing data, Multiple imputation consists of estimating the missing data multiple times to create several complete versions of an incomplete data set. All these data sets are analyzed by the same statistical procedure, and the results are pooled for interpretation. So far, no explicit rules for pooling F tests of (repeated-measures) analysis of variance have been defined. In this article we outline the appropriate procedure for the results of analysis of variance (ANOVA) for multiply imputed data sets. It involves both reformulation of the ANOVA model as a regression model using effect coding of the predictors and applying already existing combination rules for regression models. The proposed procedure is illustrated using 3 example data sets. The pooled results of these 3 examples provide plausible F and p values.     

Practice‐based research networks: Origins,overview, obstacles,and opportunities

Aims: This article focuses on the historical origins of Practice‐based Research Networks (PbRNs), particularly in the UK, and provides an overview of exemplar networks, together with a consideration of the obstacles and opportunities of such networks. Method: A selective narrative review was carried out relating to the origins of PbRNs together with a selective systematic review using the SCOPUS database to consider landmark articles in this field. Results: A historical account is provided with the origins of PbRNs deriving from pioneer GPs working alone, with their ideals then becoming embedded in family practice. Key articles are presented and also consideration given to the threats to their survival. Conceptual and developmental models of PbRNs are presented that reflect the variety of networks but also common hallmarks. Finally, the opportunities are summarised that PbRNs offer for providing a vehicle for research that is linked more closely to communities of practitioners, people, and patients. Conclusions: PbRNs provide the opportunities for including practitioners in the research effort by being part of a community. Results will have direct relevance to their practice and advances in data analysis provide more valid means of analysing data. But there are also continuing threats due to lack of infrastructure funding and a gap between PbRN activity and trials methodology that needs to be addressed.     

Article Characteristics,Content, and Authorship in the Journal of Employment Counseling

This article is an analysis of general journal and article characteristics, content, and authorship for volumes 1 through 15 of the Journal of Employment Counseling, covering the years 1964 through 1978. It attempts to determine to what extent and in what ways the membership of the National Employment Counselors Association (NECA) is served by the Journal. The average length of the journal and its articles are noted as well as the number of authors and references per article. Each article is reviewed for content classification, authorship, and the author's institutional affiliation. The basic facts and overall publication trends are identified and discussed. It is noted that only a small proportion of published articles concerned Employment Service counseling techniques. The data in this article was originally prepared for the graduate course entitled “Psychology 411: Professional Problems in Psychology” at the University of Missouri-Columbia.     

Methodological issues in prevention research: An introduction to the special issue

In recent years increased attention has been directed to prevention research as a means of solving the multitude of complex social and health problems which confront individuals and their societies. Abuse of substances, behavioral dysfunctions, violence, emotional disorders, educational failures, unwanted pregnancies and sexually transmitted diseases are but a few examples of these most difficult problems. As our recognition of the need for sound prevention strategies has grown, so has our sophistication in designing prevention research studies to evaluate the effectiveness of these new strategies. And that sophistication has brought new challenges, some of which are capable of stifling progress because of their complexity. This problem is certain to grow in importance as interventions with multiple components are used more frequently to meet the challenges of the complex social and health problems we face. This special issue evolved out of the recognition that prevention researchers are confronted by a myriad of difficult methodological issues which have inhibited progress in this area. The articles in the issue present innovative methodological solutions designed to overcome these problems so the field can move forward. Editor's Note: Dr. Edward Seidman edited Methodological Issues in Prevention Research while serving as Associate Editor for Methodology.     

Quality adjusted survival analysis: A neglected application of the quality of well-being scale

Abstract

Background In survival analysis, those who are alive are statistically coded as 1.0 while those who are dead are coded as 0.0. Since everyone who remains alive is given the same score, a person confined to bed with an irreversible coma is alive and is counted the same as someone who is active and asymtomatic. The Quality of Well-being (QWB) scale defines levels of wellness on the continuum between death and optimum function and integrates morbidity and mortality into the same number. This paper demonstrates the effect of including mortality in QWB estimates for male adults with HIV infection.

Method This study involves follow-up of a cohort of 386 male adults participating in the San Diego HIV Neurobehavioral Research Center (HNRC). Patients were evaluated using the QWB at enrollment and at six month intervals. All patients were classified into three stages of HIV disease according to the Center for Disease Control (CDC) classification: CDC IV (symptomatic HIV disease), CDC II or III (asymptomatic infection) and uninfected male controls.

Results QWB scores were calculated with and without mortality included for men in each CDC class who completed a one year (N = 148) or two year follow-up (N = 60). At each evaluation, there were significant differences among CDC classes and inclusion of deaths increased the variance accounted for by CDC class at each evaluation.

Conclusions HIV infection has significant impacts upon both morbidity and mortality. Survival analysis captures only the mortality dimension, while quality adjusted survival analysis using the QWB includes both dimensions. We propose quality adjusted survival analysis as a more sensitive method for assessing outcome in HIV disease and other health conditions.     

What Causes the Mean Bias of the Likelihood Ratio Statistic with Many Variables?

Abstract

Survey data often contain many variables. Structural equation modeling (SEM) is commonly used in analyzing such data. However, conventional SEM methods are not crafted to handle data with a large number of variables (p). A large p can cause T_ml, the most widely used likelihood ratio statistic, to depart drastically from the assumed chi-square distribution even with normally distributed data and a relatively large sample size N. A key element affecting this behavior of T_ml is its mean bias. The focus of this article is to determine the cause of the bias. To this end, empirical means of T_ml via Monte Carlo simulation are used to obtain the empirical bias. The most effective predictors of the mean bias are subsequently identified and their predictive utility examined. The results are further used to predict type I errors of T_ml. The article also illustrates how to use the obtained results to determine the required sample size for T_ml to behave reasonably well. A real data example is presented to show the effect of the mean bias on model inference as well as how to correct the bias in practice.     

Nonsuicidal Self‐Injury Is Predictive of Suicide Attempts Among Individuals with Mood Disorders

Nonsuicidal self‐injury (NSSI) prior to age 18 was evaluated as a risk factor for adulthood suicide attempt (SA). Archival data from 222 mood‐disordered participants were analyzed using multivariate Cox proportional hazards analysis. Participants with a youth SA were excluded. The hazards of SA among adult participants with a history of youth NSSI were twice than those of mood‐disordered participants without youth NSSI (hazard ratio = 2.00, 95% confidence interval = 1.16–3.44, p = .01). Moreover, participants who had both youth and adult NSSI attempted suicide significantly earlier than participants who began NSSI as an adult. Youth NSSI is associated with persistent, elevated SA risk in adulthood.     

What is Epistemological Violence in the Empirical Social Sciences?

This article discusses the meaning of epistemological violence in the empirical social sciences. It is argued that the concept is closer to personal than to structural violence in that it has a subject, an object, and an action, even if the violence is indirect and nonphysical: the subject of violence is the researcher, the object is the Other, and the action is the interpretation of data that is presented as knowledge. Using a hypothetical example, the problem of interpretation in empirical research on the Other is discussed. Epistemological violence refers to the interpretation of social-scientific data on the Other and is produced when empirical data are interpreted as showing the inferiority of or problematizes the Other, even when data allow for equally viable alternative interpretations. Interpretations of inferiority or problematizations are understood as actions that have a negative impact on the Other. Because the interpretations of data emerge from an academic context and thus are presented as knowledge, they are defined as epistemologically violent actions. Problems, consequences, and practices surrounding this concept are discussed.     

Twice random,once mixed: Applying mixed models to simultaneously analyze random effects of language and participants

Psychologists, psycholinguists, and other researchers using language stimuli have been struggling for more than 30 years with the problem of how to analyze experimental data that contain two crossed random effects (items and participants). The classical analysis of variance does not apply; alternatives have been proposed but have failed to catch on, and a statistically unsatisfactory procedure of using two approximations (known as F ₁ and F ₂) has become the standard. A simple and elegant solution using mixed model analysis has been available for 15 years, and recent improvements in statistical software have made mixed models analysis widely available. The aim of this article is to increase the use of mixed models by giving a concise practical introduction and by giving clear directions for undertaking the analysis in the most popular statistical packages. The article also introduces the djmixed add-on package for SPSS, which makes entering the models and reporting their results as straightforward as possible.     

Men,Women, and Religiosity in Northern Ireland: Testing the Theories

ABSTRACT

Previous research suggests that females are more religious than males. Four theories have been put forward to explain this. This article uses cross-sectional survey data from the 2008 Northern Ireland Life and Times Survey to test two of these theories, based on a newly developed scale measuring religiosity. The analysis indicates strong support for the socialisation theory, but not necessarily for structural location. Separate analysis for men and women indicates a similar pattern, although the effect of individual variables is different for men and women. The article concludes with a discussion of measurement issues.     

Exploratory regression analysis: A tool for selecting models and determining predictor importance

Linear regression analysis is one of the most important tools in a researcher’s toolbox for creating and testing predictive models. Although linear regression analysis indicates how strongly a set of predictor variables, taken together, will predict a relevant criterion (i.e., the multiple R), the analysis cannot indicate which predictors are the most important. Although there is no definitive or unambiguous method for establishing predictor variable importance, there are several accepted methods. This article reviews those methods for establishing predictor importance and provides a program (in Excel) for implementing them (available for direct download at . The program investigates all 2 ^p – 1 submodels and produces several indices of predictor importance. This exploratory approach to linear regression, similar to other exploratory data analysis techniques, has the potential to yield both theoretical and practical benefits.     

A Spiritual Revolution in Denmark?

ABSTRACT

Based on data from the Danish part of the European Values Study 1981–2008, this article explores the validity of the claim for a spiritual revolution as proposed by Paul Heelas and Linda Woodhead. The article suggests an operationalisation of spirituality. The results of the analyses are that religious values—Christian faith as well as spirituality—tend to be stable over an individual’s life course. This suggests that, if there is a spiritual revolution, it must be the product of cohort replacement. If a spiritual revolution is taking place, Christian faith would be expected to decline in younger cohorts while spirituality would increase, but an analysis of cohort support for Christian faith and spirituality from 1981 to 2008 shows that both were constant across cohorts. Thus Danish data contain no indication that a spiritual revolution is taking place or will take place. Finally, we show that, contrary to theoretical expectations, spirituality and Christian faith are strongly correlated. A closer analysis reveals an indirect and more complicated support for parts of the theory since the two variables are explained by different factors and it shows that Christian faith, but not spirituality, is correlated with morality.     

A meta-ethnography of parents’ experiences of their children’s life-limiting conditions

ABSTRACT

As many children’s life-limiting illnesses (LLCs) are now often viewed as curable, there is an inevitable tension between providing good treatment and addressing patients and their families’ needs. For health care providers to provide optimal care, they must understand parents’ experiences of illness. Therefore, this article provides a meta-ethnography of parents’ experiences of their children’s LLCs by examining the findings of existing interpretative phenomenological analysis studies. Seventeen studies were included, which allowed the development of a conceptual model. Two multifaceted concepts emerged from the data, namely living in a bounded and polarised space and living in a collapsed time, and these are discussed with reference to their subconcepts. Recommendations for future research and practice are provided.     

A Social Network Analysis of Friendship and Spiritual Support in a Religious Congregation

Religious congregations are social settings where people gather together in community to pursue the sacred (Pargament, 2008). Such settings are important to understand as they provide a context for individuals to develop relationships, share ideas and resources, and connect individuals to larger society (Todd, 2017a). Yet, research to date has not deeply examined the inherently relational nature of religious congregations. Thus, in this study, we used social settings theory (Seidman, 2012; Tseng & Seidman, 2007) to develop and test hypotheses about relationships within one Christian religious congregation. In particular, we used social network analysis to test hypotheses about relational activity, popularity, and homophily for friendship and spiritual support types of relational links. Our findings demonstrate how relational patterns may be linked to participation in congregational activities, occupying a leadership role, a sense of community and spiritual satisfaction, stratification, socialization, and spiritual support. Overall, this advances theory and research on the relational aspects of religious congregations, and more broadly to the literature on social settings. Limitations, directions for future research, and implications for theory and religious congregations also are discussed.     

Comparing Journal of Consumer Psychology and Journal of Consumer Research

The Journal of Consumer Psychology (JCP) was created in 1992 partly in response to what was interpreted by some as a shift in the methodological focus of the Journal of Consumer Research (JCR). JCR began to increase its accommodation of postmodern approaches, compared to more positivistic approaches. JCP's mission was thus perceived by some to be more methodologically homogeneous, with a greater focus on traditional experimental psychology in the domain of consumer behavior. Is JCR really more methodologically diverse than JCP? In what other ways are the two journals similar or different? This article attempts to answer these questions with an in‐depth analysis of the articles published in both journals from 1992 to 1998. The articles are reviewed in terms of overall output, authorship, content, research design, and data analysis. Conclusions and implications are included.     

The Self As a Complex Adaptive System Part II: Levels of Analysis and the Position of the Observer

This article continues the project begun in the previous article titled: “The Self as a Complex Adaptive System. Part I: Complexity, Metapsychology, and Developmental Theories” (Palombo, 2013). Using systems theory and a complexity perspective, that article provided a critique of psychoanalytic developmental theories. This contribution addresses some of the methodological issues related to data collection on development and the effects of the observer on the observed. It introduces the Level of Analysis perspective as a heuristic that permits the use of a complexity view applicable to the construct of the self as a complex adaptive system. It proposes three levels, each of which is associated with a platform from which phenomena are observed, a neuropsychological level (L-1), an introspective level (L-2), and an interpersonal level (L-3). The article concludes with a plea for a unifying psychoanalytic paradigm that brings together the data from these three levels and that would lay the groundwork for a clinical theory that would bring together the major existing psychoanalytic theories.