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Missing values in data impede the task of inference for population parameters of interest. Multiple Imputation (MI) is a popular method for handling missing data since it accounts for the uncertainty of missing values. Inference in MI involves combining point and variance estimates from each imputed dataset via Rubin’s rules. A sufficient condition for these rules is that the estimator is approximately (multivariate) normally distributed. However, these traditional combining rules get computationally cumbersome for multicomponent parameters of interest, and unreliable at high rates of missingness (due to an unstable variance matrix). New combining rules for univariate F- and Beta-statistics from multiply-imputed data are proposed for decisions about multicomponent parameters. The proposed combining rules have the advantage of being computationally convenient since they only involve univariate F- and Beta-statistics, while providing the same inferential reliability as the traditional multivariate combining rules. Simulation study is conducted to demonstrate that the proposed method has good statistical properties of maintaining low type I and type II error rates at relatively large proportions of missingness. The general applicability of the proposed method is demonstrated within a lead exposure study to assess the association between lead exposure and neurological motor function.

Researchers increasingly take advantage of the comparative case design to build theory, but the degree of case dependence is occasionally discussed and theorized. We suggest that the comparative case study design might be subject to an often underappreciated threat—dependence across cases—under certain conditions. Using research on innovation diffusion as an illustration, we explore the role of social linkages across cases when building theory through comparison and contrast between cases. We develop an agent-based simulation, grounded by comparative case research about innovation diffusion, as novel way to study the implications of case dependence in theory building using multiple-case study research. Our simulation results suggest that the degree of case dependence has a nontrivial bearing on innovation diffusion experienced by case entities, specifically when the researcher draws a few case entities operating in a highly interconnected industry. Under these conditions, overlooking the degree of case dependence might weaken newly built theory against commonly held standards of internal validity and external validity in inductive research. We conceptualize the issue of case dependence as a concern about researchers’ bounded rationality. Accordingly, we build on our findings to provide actionable advice aiming to alleviate this concern while being amendable to the variety of approaches to build theory from multiple cases in social sciences.

This paper untangles the complex realities of Sexual Reproductive Health and Rights education in Uganda based on a Participatory Action Research with staff and volunteers of an NGO. A detailed portrait is offered of the dilemmas faced by the team around value-contradictions in this culturally sensitive domain, the complex nature of change, programme targets and community expectations. Through double loop learning methodology, the Team reflected on their own mental models and strategies used in dealing with these dilemmas and reframed their action theories towards more effective collaboration with learners and community members. The research process and outcomes illustrate the transformative power of reflection and double loop learning; resulting in practical guidance for education NGOs facing dilemmas in community collaboration.

Conventional advice discourages controlling for postoutcome variables in regression analysis. By contrast, we show that controlling for commonly available postoutcome (i.e., future) values of the treatment variable can help detect, reduce, and even remove omitted variable bias (unobserved confounding). The premise is that the same unobserved confounder that affects treatment also affects the future value of the treatment. Future treatments thus proxy for the unmeasured confounder, and researchers can exploit these proxy measures productively. We establish several new results: Regarding a commonly assumed data-generating process involving future treatments, we (1) introduce a simple new approach and show that it strictly reduces bias, (2) elaborate on existing approaches and show that they can increase bias, (3) assess the relative merits of alternative approaches, and (4) analyze true state dependence and selection as key challenges. (5) Importantly, we also introduce a new nonparametric test that uses future treatments to detect hidden bias even when future-treatment estimation fails to reduce bias. We illustrate these results empirically with an analysis of the effect of parental income on children’s educational attainment.

This article discusses anonymizing elite interviewees. Based on our experiences with interviewing professional elites and ultra-elites in different research projects, we describe how the types of conflicts involving analysis and publication change when interviewees are not promised anonymity. We discuss how contextualizing the elite positions of anonymized interviewees becomes increasingly difficult in interviews with persons who hold prestigious positions of authority and are interviewed in their official capacity. Masking interviewees can create conflicts with regard to the researcher’s presentation of results, the transparency of the research and the ability of interviewees to talk back. We show how working with non-anonymized interviewees – and even using excerpts from interviews on public radio – can be an option in qualitative research. However, non-anonymized interviews with elites should be considered only in some instances and may seriously hamper the validity of the material in other cases.

Current interrater reliability (IRR) coefficients ignore the nested structure of multilevel observational data, resulting in biased estimates of both subject- and cluster-level IRR. We used generalizability theory to provide a conceptualization and estimation method for IRR of continuous multilevel observational data. We explain how generalizability theory decomposes the variance of multilevel observational data into subject-, cluster-, and rater-related components, which can be estimated using Markov chain Monte Carlo (MCMC) estimation. We explain how IRR coefficients for each level can be derived from these variance components, and how they can be estimated as intraclass correlation coefficients (ICC). We assessed the quality of MCMC point and interval estimates with a simulation study, and showed that small numbers of raters were the main source of bias and inefficiency of the ICCs. In a follow-up simulation, we showed that a planned missing data design can diminish most estimation difficulties in these conditions, yielding a useful approach to estimating multilevel interrater reliability for most social and behavioral research. We illustrated the method using data on student-teacher relationships. All software code and data used for this article is available on the Open Science Framework: https://osf.io/bwk5t/. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Zusammenfassung. In den vergangenen Jahren nahm die Zahl der nicht-traditionell ausgebildeten Lehrkräfte in Deutschland kontinuierlich zu. Vor diesem Hintergrund untersucht der vorliegende Beitrag, inwiefern sich Quereinsteiger und traditionell ausgebildete Lehramtsanwärter im Vorbereitungsdienst hinsichtlich ihrer professionellen Kompetenz unterscheiden. Die dafür genutzten Daten stammen aus dem Projekt COACTIV-R, in dem 770 traditionell ausgebildete Lehramtsanwärter und 72 Quereinsteiger für das Fach Mathematik untersucht wurden. Multivariate Kovarianzanalysen zeigen, dass Quereinsteiger über ein ähnliches fachliches und fachdidaktisches Wissen verfügen, aber niedrigere Werte im Test zum pädagogisch-psychologischen Wissen aufweisen als traditionell ausgebildete Lehramtsanwärter. Keine signifikanten Unterschiede zeigen sich in den motivationalen Orientierungen und in den Überzeugungen. Signifikante Unterschiede zeigen sich jedoch in den selbstregulativen Fähigkeiten. Die Ergebnisse werden vor dem Hintergrund aktueller Befunde bezüglich der Lehrkräfteausbildung und der Rekrutierung von Lehrkräften diskutiert.

Given the challenges to the notion of objectivity posed by social psychological research on investigator effects, constructivist and critical epistemological perspectives, and the introduction of qualitative research methods in psychology, the investigators examined how leading methodologists understand the function of objectivity and subjectivity in psychological science. The aim of the study was to learn how contemporary methodologists view these issues so as to communicate converging perspectives to the field and inform methods education. A brief historical review of the concept of objectivity in psychology is presented to contexualize this examination. Eleven accomplished methodologists with expertise in a range of methods and epistemological perspectives were interviewed. Findings from a grounded theory analysis demonstrated that all the participants expressed concern about the belief that science is unaffected by scientists' perspectives, believing researchers and educators should problematize this perspective. Recommendations from participants included that science be viewed as a value-laden endeavor in which scientists systematically conduct research from multiple epistemological perspectives, and/or utilize diverse methods tailored to address their questions. Scientific procedures were detailed that could curtail dangers of either unchecked subjectivity or a false sense of objectivity. A functional analysis of these constructs, objectivity and subjectivity, suggested they both serve a similar scientific and an ethical purpose-to prevent the premature foreclosure of possible understanding because of the expectations of researchers. The mainstreaming of disclosures about the perspectives and positions of investigators, as well as their management, and the implementation of epistemological and methodological pluralism are encouraged to support this ethic. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Abstract. In this paper, we attempted to detect the effect of provided answers on those that succeed them, the “item proximity effect,” within a questionnaire with randomized item order for each respondent. In two studies, we administered personality inventories to two samples of mostly undergraduate students, consisting of 742 and 205 respondents, respectively. We expected to see a strong item proximity effect that quickly diminishes with higher item distances, but we found no evidence of such effect in the data. Thus, we failed to conceptually replicate the findings of previous studies. After discussing the probable causes for these discrepancies, we argue that a general item proximity effect does not need to be considered a major factor when employing and evaluating common psychological inventories with randomized item order for research purposes.

Multilevel structural equation modeling (MSEM) allows researchers to model latent factor structures at multiple levels simultaneously by decomposing within- and between-group variation. Yet the extent to which the sampling ratio (i.e., proportion of cases sampled from each group) influences the results of MSEM models remains unknown. This article explores how variation in the sampling ratio in MSEM affects the measurement of Level 2 (L2) latent constructs. Specifically, we investigated whether the sampling ratio is related to bias and variability in aggregated L2 construct measurement and estimation in the context of doubly latent MSEM models utilizing a two-step Monte Carlo simulation study. Findings suggest that while lower sampling ratios were related to increased bias, standard errors, and root mean square error, the overall size of these errors was negligible, making the doubly latent model an appealing choice for researchers. An applied example using empirical survey data is further provided to illustrate the application and interpretation of the model. We conclude by considering the implications of various sampling ratios on the design of MSEM studies, with a particular focus on educational research.

In data collected from virtual learning environments (VLEs), item response theory (IRT) models can be used to guide the ongoing measurement of student ability. However, such applications of IRT rely on unbiased item parameter estimates associated with test items in the VLE. Without formal piloting of the items, one can expect a large amount of nonignorable missing data in the VLE log file data, and this is expected to negatively affect IRT item parameter estimation accuracy, which then negatively affects any future ability estimates utilized in the VLE. In the psychometric literature, methods for handling missing data have been studied mostly around conditions in which the data and the amount of missing data are not as large as those that come from VLEs. In this article, we introduce a semisupervised learning method to deal with a large proportion of missingness contained in VLE data from which one needs to obtain unbiased item parameter estimates. First, we explored the factors relating to the missing data. Then we implemented a semisupervised learning method under the two-parameter logistic IRT model to estimate the latent abilities of students. Last, we applied two adjustment methods designed to reduce bias in item parameter estimates. The proposed framework showed its potential for obtaining unbiased item parameter estimates that can then be fixed in the VLE in order to obtain ongoing ability estimates for operational purposes.

Canadian prison-based arts and other programming are limited at best. Even the country’s Correctional Investigator, or prison-ombudsperson, has critiqued the lack of meaningful options in which prisoners can engage. Those programs that do exist tend to be focused on the logic of penal rehabilitation, with the end goal of reducing recidivism. In this article, we showcase the evaluation of a 9-week arts program in a women’s prison, the aim of which was to build community and foster artistic engagement, thus running counter to normative carceral logics.

Prison systems, with the ability to reject or approve applications for conducting research with incarcerated populations, function as shapers of carceral knowledge and thus can potentially close opportunities for new qualitative studies as well as affect the quality and richness of the data obtained. This article describes a collaborative research process wherein access to current prisoners was not granted, and only former prisoners who were not on parole were eligible to participate in the study. We provide a unique reflective analysis of how access barriers altered the scope of our research and may have impacted our findings were it not for a change in our recruitment plan. We also incorporate insights from multiple literatures that speak to the value, challenges, and ethical concerns associated with doing research with former prisoners. Our contribution to the qualitative carceral literature sparks new questions worthy of further in-depth exploration, in particular how to more meaningfully involve former prisoners in the research process.

The experiences of Black women educators are important, and yet their personal and professional experiences are rarely included as part of the faculty narrative at most North American higher education institutions. The continued normalization of White Supremacy and androcentricity, within North American higher education, maintain systems of oppression that perpetuate the systematic marginalization of Black women within the faculty ranks. The purpose of this study was to understand the experiences of Black women educators in New Mexico's higher education institutions. With a grounding in Black Womanist and Critical Race Theories, this qualitative research study employed snowball sampling as a means to engage ten Black women faculty members, via semi-structured interviews, in critical inquiry about their professional experiences with higher education. Study participants testified about experiences with microaggressions, discrimination, and racial battle fatigue as well as feeling intellectual, campus, and community isolation.

Many calls have been made for more research on social studies teachers’ practices and preservice training. Instructional practices employed by teachers are important for encouraging student learning. However, there is a history of social studies teachers focusing much of their time on teacher-centered instructional techniques that have not demonstrated strong learning for students. Therefore it is important to examine not just how teachers chose to teach, but also where they may have learned to teach. This study examined data from the Teaching and Learning International Survey (TALIS) 2018 of 240 secondary social studies teachers to understand what instructional practices they report employing and their feelings about their preparation. Data analysis provided direct empirical evidence of the power of teacher preparation programs to shape social studies teachers’ instructional practices well into their teaching careers.

A huge portion of what we know about how humans develop, learn, behave, and interact is based on survey data. Researchers use longitudinal growth modeling to understand the development of students on psychological and social-emotional learning constructs across elementary and middle school. In these designs, students are typically administered a consistent set of self-report survey items across multiple school years, and growth is measured either based on sum scores or scale scores produced based on item response theory (IRT) methods. Although there is great deal of guidance on scaling and linking IRT-based large-scale educational assessment to facilitate the estimation of examinee growth, little of this expertise is brought to bear in the scaling of psychological and social-emotional constructs. Through a series of simulation and empirical studies, we produce scores in a single-cohort repeated measure design using sum scores as well as multiple IRT approaches and compare the recovery of growth estimates from longitudinal growth models using each set of scores. Results indicate that using scores from multidimensional IRT approaches that account for latent variable covariances over time in growth models leads to better recovery of growth parameters relative to models using sum scores and other IRT approaches. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Zusammenfassung. Im vorliegenden Beitrag wird die theoriegeleitete Entwicklung und Erprobung eines Instrumentes zur standardisierten Erfassung von Planungskompetenzen angehender Lehrkräfte im Fach Sachunterricht dokumentiert, auf dessen Grundlage das in Nordrhein-Westfalen 2015 als Teil des Masterstudiums implementierte Praxissemester hinsichtlich der damit intendierten Ausbildung von Planungsfähigkeiten evaluiert werden soll. Ausgehend von einem Rahmenmodell, das die Instrumententwicklung in vier zentrale Bereiche untergliedert, wird zunächst das theoretische Konstrukt sachunterrichtlicher Planungskompetenz in Form eines Kompetenzmodells konzeptualisiert. Auf Grundlage eines performanznahen Kompetenzverständnisses erfolgt die Operationalisierung in Form von Qualitätsstandards, durch die das Können der Probanden aus der schriftlichen Bearbeitung von Vignetten inhaltsanalytisch rekonstruiert werden kann. Ein Kodiermanual sichert die Objektivität und formuliert Regeln für die Vergabe von Punkten, durch die mithilfe des dichotomen Raschmodells die individuellen Kompetenzausprägungen geschätzt werden können. Zur Analyse der psychometrischen Qualität des entwickelten Instrumentes wurde eine Pilotierungsstudie mit 106 Studenten durchgeführt. Ein Vergleich konkurrierender Messmodelle mit Methoden der Item-Response-Theorie weist auf Vorteile einer eindimensionalen Modellierung der fokussierten Kompetenz hin. Die Ergebnisse einer durchgeführten Rasch-Analyse sowie die Betrachtung klassischer Kennwerte belegen zudem die Modellkonformität der entwickelten Qualitätsstandards als Items des Testinstrumentes und zeigen, dass die Messung sachunterrichtlicher Planungskompetenz durch das entwickelte Instrument grundsätzlich objektiv, reliabel und valide realisiert werden kann. Der praktische Nutzen des entwickelten Instrumentes für die angestrebte Wirksamkeitsanalyse des Praxissemesters, Möglichkeiten zur Weiterentwicklung sowie Limitationen werden abschließend zusammenfassend diskutiert.

The body of research on civic education points to the importance of teachers creating open democratic environments, leading to what has been termed the political classroom. This yearlong study of an Israeli multicultural and bilingual high school civics course, in which students from different citizenship status participated, presents a case in which teachers were unsuccessful in achieving this goal, raising the question of what limited this class's potential to create an educational environment where democratic discourses could have taken place? The main argument points to Israel's current disputative political environment that led to the enactment of four educational mechanisms that resulted in such a futile reality. These included: conflicting objectives, avoiding discussion of controversial issues, implementing traditional teaching practices, and overlooking language issues. The neo-liberal educational environment and a culture of fear and self-censorship were both identified as a common explanation to these, leading to an educational reality in which there was a detach between the lessons and the students’ transcultural lived political experiences. From a methodological perspective, the study illuminates the importance of focusing on such unsuccessful cases, examining their elements, and understanding what influences them.

Social studies teachers are often reported as remaining reluctant to engage their students in discussions of contemporary social and political issues. It is therefore critically important to investigate instances of such discussions when they do occur. This paper, part of a larger qualitative study that included six middle and high school classrooms and 24 observed discussions, considers how students are positioned in classroom discussions of social and political issues. By thinking in terms of positions and Ellsworth's (1997) notion of “modes of address”, the authors conceptualize political discussions in terms of the delicate relations between intent and outcome, the social and personal, certainty and surprise. This paper identifies three modes through which students are invited into relation to social and political life via discussions of current topics: task-oriented participants, distanced commentators, and/or as implicated citizens.

Verbal protocol methodology is used to examine how fourth-grade students construct meaning as they read and respond to two informational social studies texts. Results indicate most students are active readers, often engaging in higher-level comprehension strategies and critical thinking as they read independently. However, critical thinking and comprehension processes are not often captured in their responses to end-of-reading questions (ERQ), which as a result have limited scope and utility for guiding social studies instruction. Results also indicate that when students change their patterns of strategy use for reading and responding to text in response to a change in text, they are more successful on the ERQ than when their strategy use remains stagnant.

This article focuses on article 28 (right to education), article 29 (goals of education) and article 30 (children from minority or indigenous groups) of the United Nations Convention on the Rights of the Child (UNCRC) and their implementation in the several national policies of Western Europe, especially the UK and Ireland, and to a lesser extent, France. The present research looked more particularly into the situation of children from two communities: Gypsy, Roma and Travellers (referred to as GRT) and Irish Travellers. Although they are from different backgrounds, the analysis proved relevant because of the bridges that exist between their cultures and lifestyles, and because of their minority status within larger dominant communities, placing their children in the frontline of the UNCRC battle. The text of the UNCRC itself was a starting point. The research was mainly based on a series of reports from governments, from organizations such as the Traveller Movement, on articles from newspapers, and testimonies from GRT children and Irish Travellers. The results showed that the implementation of articles 28 to 30 of the UNCRC was being by and large slowly carried out by the countries under study. Yet, national disparities were evident. Also, their national policies revealed different contexts. Ireland seemed to be paving the way for the inclusion of minorities within the educational system.

Abstract. This study reports the process of item reduction of the Enright Forgiveness Inventory – EFI, a measure of interpersonal forgiveness, from 60 to 30 items for a more practical assessment of this construct. Data from the US were used in the creation of the new measure and applied to seven nations: Austria, Brazil, Israel, South Korea, Norway, Pakistan, and Taiwan. The question was: do the best EFI-30 items from the US have discriminative power in seven other cultures? Results provided the psychometric evidence for the reduced version of the EFI-30 across cultures. The discrimination values are positive, suggesting that the selected items have the sensitivity to differentiate accurately people with different degrees of forgiveness and good psychometric properties of internal consistency.

A growing number of publications focus on estimating Gaussian graphical models (GGM, networks of partial correlation coefficients). At the same time, generalizibility and replicability of these highly parameterized models are debated, and sample sizes typically found in datasets may not be sufficient for estimating the underlying network structure. In addition, while recent work emerged that aims to compare networks based on different samples, these studies do not take potential cross-study heterogeneity into account. To this end, this paper introduces methods for estimating GGMs by aggregating over multiple datasets. We first introduce a general maximum likelihood estimation modeling framework in which all discussed models are embedded. This modeling framework is subsequently used to introduce meta-analytic Gaussian network aggregation (MAGNA). We discuss two variants: fixed-effects MAGNA, in which heterogeneity across studies is not taken into account, and random-effects MAGNA, which models sample correlations and takes heterogeneity into account. We assess the performance of MAGNA in large-scale simulation studies. Finally, we exemplify the method using four datasets of post-traumatic stress disorder (PTSD) symptoms, and summarize findings from a larger meta-analysis of PTSD symptom.

In this article we extend the framework of explanatory mixed IRT models to a more general class called explanatory additive IRT models. We do this by augmenting the linear predictors in terms of smooth functions. This development offers many new modeling options such as the inclusion of nonlinear covariate effects, the specification of various temporal and spatial dependency patterns, and parameter partitioning across covariates. We use integrated nested Laplace approximation (INLA) for accurate and computationally efficient estimation of the parameters. Uninformative, weakly informative, and informative prior settings for the hyperparameters are discussed. Running time experiments and Monte Carlo parameter recovery simulations are performed in order to study the accuracy and computational efficiency of INLA when applied to the proposed explanatory additive IRT model class. Using a real-life dataset, a variety of application scenarios is explored, and the results are compared with classical maximum likelihood estimation when possible. R code is included in the supplemental materials to allow readers to fully reproduce the examples computed in the paper.

The goal of this article is to clarify and unravel the complexity and challenges of improving teaching quality, based on measuring teaching quality and feeding back the results to teachers. We analyze different conceptualizations of teaching quality, and synthesize a framework for conceptualizing teaching quality in educational practice. We explain the pros and cons of four types of instruments for measuring teaching quality. Next, we scrutinize the requirements of effectively feeding back teaching quality data and the requirements for effective actions to improve teaching quality. We conclude with implications for improving the consequential validity of teaching quality measurements.

Background Functional neurological disorder is defined by symptoms not explained by the current model of disease and its pathophysiology. It is found in 8.4% of patients presenting as acute stroke. Treatment is difficult and recurrence rates are high. We introduced hypnotherapy as a therapeutic option in addition to standard stroke unit care. Methods This is an observational study of successive patients with functional neurological disorder presenting as acute stroke treated with hypnotherapy between 1 April 2014 and 1 February 2018. The diagnosis of functional neurological disorder was confirmed by clinical examination and computed tomography/magnetic resonance imaging. Hypnosis was delivered by a hypnotherapy trained stroke physician using imagery for induction. A positive response was defined as a National Institutes of Health Stroke score reduction to 0 or by ≥4 points posthypnotherapy. Costs were calculated as therapist time and benefits as reduction in disability/bed days. Results Sixty-eight patients (mean age 36.4 years, 52 (76%) females, mean baseline National Institutes of Health Stroke 5.0 (range 1–9)) were included. Two patients (3%) could not be hypnotized. Fifty-eight 58 (85%) responded, 47 (81%) required one treatment session, while 19% needed up to three sessions for symptomatic improvement. No adverse events were observed. Disability (modified Rankin Scale) reduced from a mean of 2.3 to 0.5 resulting in an average cost saving of £1,658 per patient. Most (n = 50, 86%) remained well without recurrence at six-month follow-up. Conclusions In this case series, hypnotherapy was associated with rapid and sustained recovery of symptoms. A prospective randomized controlled study is required to confirm the findings and establish generalizability of the results.

Psychological research often builds on between-group comparisons of (measurements of) latent variables; for instance, to evaluate cross-cultural differences in neuroticism or mindfulness. A critical assumption in such comparative research is that the same latent variable(s) are measured in exactly the same way across all groups (i.e., measurement invariance). Otherwise, one would be comparing apples and oranges. Nowadays, measurement invariance is often tested across a large number of groups by means of multigroup factor analysis. When the assumption is untenable, one may compare group-specific measurement models to pinpoint sources of noninvariance, but the number of pairwise comparisons exponentially increases with the number of groups. This makes it hard to unravel invariances from noninvariances and for which groups they apply, and it elevates the chances of falsely detecting noninvariance. An intuitive solution is clustering the groups into a few clusters based on the measurement model parameters. Therefore, we present mixture multigroup factor analysis (MMG-FA) which clusters the groups according to a specific level of measurement invariance. Specifically, in this article, clusters of groups with metric invariance (i.e., equal factor loadings) are obtained by making the loadings cluster-specific, whereas other parameters (i.e., intercepts, factor (co)variances, residual variances) are still allowed to differ between groups within a cluster. MMG-FA was found to perform well in an extensive simulation study, but a larger sample size within groups is required for recovering more subtle loading differences. Its empirical value is illustrated for data on the social value of emotions and data on emotional acculturation. (PsycInfo Database Record (c) 2022 APA, all rights reserved). ispartof: Psychological Methods vol:27 issue:3 pages:281-306 ispartof: location:United States status: published

This paper presents a novel Bayesian variable selection approach that accounts for the sign of the regression coefficients based on multivariate one-sided tests. We propose a truncated g prior to specify a prior distribution of coefficients with anticipated signs in a given model. Informative priors for the direction of the effects can be incorporated into prior model probabilities. The best subset of variables is selected by comparing the posterior probabilities of the possible models. The new Bayesian one-sided variable selection procedure has higher chance to include relevant variables and therefore select the best model, if the anticipated direction is accurate. For a large number of candidate variables, we present an adaptation of a Bayesian model search method for the one-sided variable selection problem to ensure fast computation. In addition, a fully Bayesian approach is used to adjust the prior inclusion probability of each one-sided model to correct for multiplicity. The performance of the proposed method is investigated using several simulation studies and two real data examples.

This collective paper on radicalization and violent extremism part of the 'Philosophy of education in a new key' initiative by Educational Philosophy and Theory brings together some of the leading contemporary scholars writing on the most pressing epistemological, ethical, political and educational issues facing post-9/11 scholarship on radicalization and violent extremism. Its overall aim is to move beyond the 'conventional wisdom' associated with this area of scholarly research best represented by its many slogans, metaphors and other thought-terminating cliches. By providing conceptual lenses on issues previously compartmentalized primarily [or even exclusively] in security and intelligence studies or at the fringes of scholarly interest, radicalization and violent extremism turn out to be much more complex than 'radicalization studies' has been eager to acknowledge.

Abstract. Job crafting is a multidimensional construct that can be conceptualized both at the general level and at the daily level. Several researchers have used aggregated scores across the dimensions of job crafting, to represent an overall job crafting construct. The purpose of the research presented herein is to investigate the factor structure of the general and daily versions of the job crafting scale developed by Petrou et al., (2012) (PJCS), using parametric multidimensional Item Response Theory (IRT) models. A sample of 675 employees working on different occupational sectors completed the Greek version of the scales. Results are in line with theoretical underpinnings and suggest that, although a bifactor IRT model offers an adequate fit, a correlated factors IRT model is more appropriate for both versions of the PJCS. Results caution against using aggregated scores across the dimensions of PJCS for both the general and daily versions.

Purpose We aimed to investigate measurement invariance (MI) in the European Organisation for research and treatment of cancer quality of life questionnaire core 30 (EORTC QLQ-C30) in a heterogeneous sample of patients with cancer. Methods Data from 12 studies within the PROFILES registry were used for secondary analyses (n = 7007). We tested MI by successive restrictions on thresholds, loadings, and intercepts across subgroups based on primary cancer sites, age, sex, time since diagnosis, and life stage, using multigroup confirmatory factor analysis (MGCFA) for ordered categorical measures. We also evaluated the impact of potentially miss-specified parameter equality across groups on latent factor means by releasing threshold and loading equality constraints for each item at a time. Results Results showed that the highest level of MI (invariance of thresholds, loadings, and intercepts) was found across groups based on time since diagnosis and life stage and to a lesser extent across groups based on sex, age, and primary tumor site. On item level, however, changes in the item’s associated factor means were relatively small and in most cases canceled each other out to some extent. Conclusions Given only a few instances of non-invariance in our study, there is reason to be confident that valid conclusions can be drawn from between-group comparisons of QLQ-C30 latent means as operationalized in our study. Nonetheless, further research into MI between other subgroups for the QLQ-C30 (i.e., treatment effects and ethnicity) is warranted. We stress the importance of including MI evaluations in the development and validation of measurement instruments.

This study focuses on teachers' group decision making during Dutch allocation meetings. A previous interview study showed that teachers question the objectivity of decisions due to negative interaction experiences and a lack of structure during these meetings. To characterize the structure and interaction of these meetings, 33 student allocations were observed. Results showed a variety of structures and interactions, including differences in the degree to which the meetings met criteria relevant to achieving objective allocation decisions. It can be concluded that - based on the criteria of acceptance, fairness, and transparency as used in this study - allocation meetings need to be well-prepared and substantiated, to allow for every teacher's opinion to be heard, and follow a procedure that is clear to everyone. In view of students' future school careers, it is important to pay close attention to functional interaction and structured discussions that ensure transparent, acceptable and fair decision-making.

A culture of inquiry in schools, where teachers work collaboratively andinquiry based, can contribute to the quality of education. It is assumedthat teachers of research-intensive teacher education programmes canplay an important role in creating such a culture. Little is known, however,about how these teachers function. This case-study research investigateshow primary school teachers of research-intensive teacher educationprogrammes in the Netherlands contribute to a culture of inquiry andwhich factors influence this. In five schools semi-structured interviewswere conducted with a teacher and her/his school leader. Also schoolpolicy documents were analysed and team meetings were observed. Theteachers contributed to a culture of inquiry in their schools in three ways,by 1) initiating collective critical reflection on school policy, 2) sharingknowledge with colleagues and 3) initiating innovations. According to theteachers, self-efficacy in collaboration with colleagues in inquiry-basedworking and a formal research position in the school facilitates the contribution they can make to a culture of inquiry.

Purpose Mokken scale analysis (MSA) is an attractive scaling procedure for ordinal data. MSA is frequently used in health-related quality of life research. Two of MSA's prime features are the scalability coefficients and the automated item selection procedure (AISP). The AISP partitions a (large) set of items into scales based on the observed item scores; the resulting scales can be used as measurement instruments. There exist two issues in MSA: First, point estimates, standard errors, and test statistics for scalability coefficients are inappropriate for clustered item scores, which are omnipresent in quality of life research data. Second, the AISP insufficiently takes sampling fluctuation of Mokken’s scalability coefficients into account. Methods We solved both issues by providing point estimates and standard errors for the scalability coefficients for clustered data and by implementing a Wald-based significance test in the AISP algorithm, resulting in a test-guided AISP (T-AISP), that is available for both nonclustered and clustered test scores. Results We integrated the T-AISP into a two-step, test-guided MSA for scale construction, to guide the analysis for nonclustered and clustered data. The first step is performing a T-AISP and select the final scale( s ). For clustered data, within-group dependency is investigated on the final scale(s). In the second step, the strength of the scale(s) is determined and further analyses are performed. The procedure was demonstrated on clustered item scores obtained from administering a questionnaire on quality of life in schools to 639 students nested in 30 classrooms. Conclusions We developed a two-step, test-guided MSA for scale construction that takes into account sample fluctuation of all scalability coefficients and that can be applied to item scores obtained by a nonclustered or clustered sampling design.

In this study, we aimed to identify how the learning activities elicited in a lesson study project contributed to self-perceived change in supervisors’ pedagogical content knowledge (PCK). Lesson study is a method which combines both professional and educational development. During a lesson study project, teachers collaborate in a team and develop, teach, evaluate, and redesign a research lesson. During the 4-month lesson study project described here, four supervisors designed a protocol for research supervision meetings aimed at enhancing undergraduate students’ learning. During the project, they experimented with open questioning and giving positive feedback instead of giving instruction and explanations. A mixed-methods design was used in this study. Data on the supervisors’ learning activities and PCK were gathered using learner reports, video-recordings of meetings, and exit interviews. The analyses of these data showed that the lesson study project contributed to the development of the supervisors’ PCK on instructional strategies and student understanding. The learning activity that contributed most to these changes was reflecting on their own practice and that of their students.

Home-based parental involvement in early education is linked to beneficial outcomes in children’s development and may redress unequal educational outcomes associated with family background. The type of educational activities at home and the way parents provide their support may differ across parents with and without a migration background. It is unclear whether home-based parental involvement is measured as the same construct across different origin groups. In this study, the psychometric properties of two parent-report questionnaires on home-based parental involvement were evaluated in 131 Dutch mothers of kindergarten-aged children, of whom 47% had a migration background. The dimensional structure of both questionnaires was tested with Principal Component Analysis. Multi-group confirmatory factor analyses were conducted to test for measurement invariance of the ‘Parenting Questionnaire’ across migration background. Results supported the multidimensional nature of home-based parental involvement, as formal and informal activities formed distinct components in the involvement of this diverse parent sample. In addition, measurement invariance was largely confirmed, indicating that parent’s involvement style can be validly measured across parents with and without a migration background in the Dutch context. Incorporating both formal and informal activities with involvement styles is recommended when measuring home-based parental involvement in different origin groups.

The Schwarz or Bayesian information criterion (BIC) is one of the most widely used tools for model comparison in social science research. The BIC however is not suitable for evaluating models with order constraints on the parameters of interest. This paper explores two extensions of the BIC for evaluating order constrained models, one where a truncated unit information prior is used under the order-constrained model, and the other where a truncated local unit information prior is used. The first prior is centered around the maximum likelihood estimate and the latter prior is centered around a null value. Several analyses show that the order-constrained BIC based on the local unit information prior works better as an Occam's razor for evaluating order-constrained models and results in lower error probabilities. The methodology based on the local unit information prior is implemented in the R package `BICpack' which allows researchers to easily apply the method for order-constrained model selection. The usefulness of the methodology is illustrated using data from the European Values Study., 25 pages, 4, figures, 2 tables

Bias-adjusted three-step latent class analysis (LCA) is widely popular to relate covariates to class membership. However, if the causal effect of a treatment on class membership is of interest and only observational data is available, causal inference techniques such as inverse propensity weighting (IPW) need to be used. In this article, we extend the bias-adjusted three-step LCA to incorporate IPW. This approach separates the estimation of the measurement model from the estimation of the treatment effect using IPW only for the later step. Compared to previous methods, this solves several conceptual issues and more easily facilitates model selection and the use of multiple imputation. This new approach, implemented in the software Latent GOLD, is evaluated in a simulation study and its use is illustrated using data of prostate cancer patients.

In this paper we explore Lawrence Stenhouse’s (1981) provocation that too much research has been conducted for the world and not enough for the village. This provocation has taken on additional significance in contemporary global policy contexts where neo-liberal systems of governance incorporate discourses of educational effectiveness, measurement, standards, quality and sustainable development. Reform movements draw attention to what forms of professional development are effective in the complex global-national policy agendas, with diverse cultural-historical and socio-political contexts. Furthermore, teachers’ work is changing and intensifying under neo-liberal systems of governance, specifically what they have to do to interpret and not just to implement policies. Drawing on two contrasting case studies of teacher research in England and Kazakhstan, we examine ‘outside in’ and ‘inside out’ approaches to teacher development. We problematize the concepts of teacher autonomy, the interpretational work of teachers in the context of policy intensification, and strategic compliance as a pragmatic and necessary response to policy frameworks and their intended and unintended consequences. We conclude by suggesting a hybrid, dialectical approach to professional development which sustains teacher autonomy and professionalism.

How should migration scholars navigate tensions between our ethical responsibilities to research participants and growing “open science” calls for data transparency, replication, and accountability? We elaborate a three-step process to navigate these tensions. First, researchers must understand core principles behind open-science initiatives and the mandates of research ethics boards, especially those related to privacy, confidentiality, and protection from harm, and take them seriously. Second, migration researchers must think beyond routinized or mandated procedures to carefully consider the unique vulnerabilities of migrants in their study, which depend on socio-political context. Third, if vulnerabilities are significant, migration researchers should modify (or challenge) procedures elaborated in the name of open science or routinized research ethic board mandates, if inappropriate for their study. We, thus, encourage migration scholars to engage with open-science advocates but also to educate colleagues on migrants’ vulnerabilities and to double-down on data security, including vis-à-vis government authorities, as evolving technologies continue to change research practices.

Latent variables in structural equation models do not have an observable scale. Hence researchers resort to scaling methods, such as fixed marker, effects coding, or fixed factor, to assign scales to the latent variables. The use of such procedures results in numerically different estimates, in spite of a single underlying population model. In this paper, we provide a framework which not only allows for a translation between estimates obtained under different scaling methods, but also helps to explore the relation between the underlying population parameters and their estimates, thus providing a basis for the interpretation of estimated parameters. Addition- ally, the framework proves useful for demonstrating that the choice of scaling method affects the power of the Wald test for testing parameters’ significance.

Reluctance of respondents to participate in surveys has long drawn the attention of survey researchers. Yet, little is known about what drives a respondent’s decision to answer the survey invitation early or late during the field period. Moreover, we still lack evidence on response timing in longitudinal surveys. That is, the questions on whether response timing is a rather stable respondent characteristic and what—if anything—affects change in response timing across different interviews remain open. We relied on data from a mixed-mode general population panel survey collected between 2014 and 2016 to study the stability of response timing across 18 panel waves and factors that influence the decision to participate early or late in the field period. Our results suggest that the factors which had effects on response timing are different in the mail and web modes. Moreover, we found that experience with prior panel waves affected the respondent’s decision to participate early or late. Overall, the present study advocates understanding response timing as a metric variable and, consequently, the need to reflect this in modeling strategies.

Using a phenomenographic design, this research reports on a study of a cohort (N = 22) of graduate students’ conceptualizations of difference as they progressed through the only required diversity course in a science education program at a large, urban university in the American northeast. Data collection included biweekly course reflections, a modified Pedagogy of Science Teaching Test designed with students labeled with disabilities within its contextual framing, and biweekly ‘science for all’ lessons created by the participants that were not explicitly framed to address disability. Mixed-methods data analyses addressed to what extent these graduate students developed a critical lens toward difference (i.e., expressed, imagined, and/or imposed variations in human behavior and potential) and explored to what extent these theoretical elements transferred into pragmatic applications by the participants, for example in their lesson planning, that addressed multiple interpretations of difference to provide evidence of their capabilities to bridge theory to practice. Additionally, the case of disability as a marker of difference was also paid special attention to in light of lacking analyses in multicultural science education around issues of disability exclusion and teacher biases toward this marker of difference. The data suggest that while students in this ‘urban and multicultural science education’ course appear to be able to theorize critically about multicultural issues in urban science education (as per the goal of the course), their capacities to reflect on their pedagogical decisions within contexts that contain students labeled with disabilities, and plan comprehensive ‘science for all’ classroom learning environments, remained disciplinary focused, no matter if the students labeled with disabilities were the focal marker of difference within these contexts’ demographics or not. Emergent data analysis also suggests that disability was the least recognized and interpreted marker of difference, which led to limited ways that students took up this concept in comparison with other forms of difference such as race, class, and gender. Moreover, rather than emphasizing critical pedagogies that are pertinent for transformative change in science education for all diverse populations, the participants remained focused on narrowly defined, content-specific ways of teaching and learning science. Implications for this research include focusing on the goals of courses such as this one, attending to the unique case of disability as a liminal realm of conceptualizing difference, and supporting graduate students’ needs to aid in bridging the divide between theory and practice for both more traditional markers of difference taken up by multicultural science education (e.g., race, class, and gender) as well as disability as a marker of difference that is under theorized and lacking pragmatic application within such diversity requirement courses.

Research is needed to explain in more depth what happens and why in teacher-researcher collaboration. Previous research on collaboration points out issues such as asymmetric power relations and cultural differences between professions that can potentially cause problems. This paper examines a Swedish action research project in which teachers and researchers worked together to write a textbook for pre-service teacher education. To study the collaboration, theory on recognition was used to interpret how teachers and, to some extent, researchers understand and value themselves and each other’s participation and contribution. Data was collected from a two-day dialogue meeting in the middle of the process where teachers and researchers met to discuss their on-going writing. The result shows that, through well-structured dialogues, the participants transformed their understanding and valuing of both themselves and others in relation to the task of producing new didactical knowledge. This is interpreted as transformed self-recognition for the teachers, who started to acknowledge themselves as knowledge producers. This transformation was crucial for developing the mutual recognition through which new didactical knowledge emerged as a result of the collaboration.

Discussions about texts can offer valuable opportunities for critical conversations about power and privilege. While we know such conversations are important to have in school, many teachers report feeling unprepared to facilitate them. In an effort to understand the in-the-moment decisions preservice teachers (PSTs) make in response to children’s contributions during critical conversations about texts, this qualitative, design-based study examines how PSTs responded to elementary-age children while facilitating discussions about texts in their field placements. Although various kinds of responses were made (e.g., eliciting children’s thinking, orienting children’s contributions to one another), in this analysis, we examine the moments where PSTs identified their silence as salient. Findings reveal that (1) some PSTs developing understanding of the role of talk and desire to efficiently accomplish the task did not seem to set them up to see critical conversations about texts as a space for sensemaking, and (2) other PSTs did see critical conversations about texts as spaces to engage in sensemaking but felt discomfort grappling with unanticipated issues that arose. We discuss implications for literacy researchers and teacher educators committed to supporting critical conversations with children in schools.

Assessment of treatment response in psychotherapies can be undermined by lack of longitudinal measurement invariance (LMI) in symptom self-report inventories, by measurement error, and/or by wrong model assumptions. To understand and compare these threats to validity of outcome assessment in psychotherapy research, we studied LMI, sum scores, and Davidian Curve Item Response Theory models in a naturalistic guided internet psychotherapy treatment register of 2,218 generalized anxiety disorder (GAD) patients and 3,922 depressive disorder (DD) patients (aged ≥16 years). Symptoms were repeatedly assessed by Generalized Anxiety Disorder Assessment-7 (GAD-7) or Beck Depression Inventory. The symptom self-reports adhered to LMI under equivalence testing, suggesting sum scores are reasonable proxies for disorder status. However, the standard LMI assumption of normally distributed latent factors did not hold and inflated treatment response estimates by 0.2 to 0.3 standard deviation units compared with sum scores. Further methodological research on non-normally distributed latent constructs holds promise in advancing LMI and mental health assessment.

Abstract. The current paper investigates the structural validity of the Children's Concentration and Empathy Scale (CCES), which was designed based on Montessori's developmental theory to assess, using teacher ratings, the coherence of attention-related characteristics (concentration, empathy, and normalization) in children from 1.5 to 12 years old. The dimensionality analysis was carried out using exploratory graph analysis (EGA), and the stability of the items and factors were checked using a bootstrap version of EGA, and the results contrasted to exploratory factor analysis. The results point to a four-factor structure (emotion regulation, fantasy, task engagement, and empathy) after eliminating items with low replicability across bootstrapped samples. Beyond pointing to ways to improve the CCES, our paper presents a number of data analytical strategies that can be useful for studies investigating the structural validity of measurement instruments and demonstrates how EGA can effectively be used in the scale construction and validation process. Our manuscript and results are fully reproducible and are available on the Open Science Framework.