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Abstract: Recent advancements in access to U.S. Census data now present even moderately skilled analysts with the ability to perform sophisticated and relatively more accurate human life value estimates. This article identifies the added value associated with investigations using actual census data to provide more succinct, defensible, and subject-specific estimates. An example is presented that compares three differing approaches to such estimates as a means of delineating the value associated with a more rigorous statistical approach relying on actual census data. Additionally, the appendix includes a step-by-step description ofthe analytic process used in the example described in the article. [ABSTRACT FROM AUTHOR]

In this paper, the distributions of scan statistics of inhomogeneous Poisson processes are studied. First, the distribution of the continuous scan statistic of an inhomogeneous Poisson process is approximated by the distribution of the discrete scan statistic for a sequence of Bernoulli trials with unequal probabilities of success. Next, we introduce a weighted scan statistic to adjust the inhomogeneity and the weighted continuous scan statistic is also approximated by the weighted discrete scan statistic. The finite Markov chain imbedding technique is used to obtain the exact distributions of weighted discrete scan statistics. An example using the weighted scan statistic of an inhomogeneous Poisson process for detecting DNA copy number variation is given. Numerical results and simulations are also given to illustrate our theoretical results. [ABSTRACT FROM AUTHOR]

Since the early 2000s, theorizing on incremental institutional change has made inroads in comparative historical analysis. In particular, the ideas, concepts, and theory introduced by Kathleen Thelen and her collaborators have been widely adopted by scholars. These scholars are not, however, univocally positive about the theory. Three main critiques have been plaguing the theory since its early days: the concepts it builds on lack clarity, the model of agency it uses is too static, and the theory lacks analytical power overall. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis method, this article presents a meta-analysis of the peer-reviewed empirical literature from 2005 to 2015 that applies this theory. It seeks to better understand the reach of the critiques expressed, as this may provide a starting point for improvement. It finds considerable quantitative support for the critiques, and uncovers an additional problematic issue: the tendency for concept stretching and concept proliferation by scholars seeking to overcome the shortcomings of the theory. Paradoxically, concept stretching and proliferation only further reduce the analytical power of the theory. The article concludes with suggestions for improvement of the development and application of the theory. [ABSTRACT FROM AUTHOR]

This article is based on an invited speech given at Massey University in August 2016 where Tolich revealed the inspiration for his 25-year sociological analysis of research ethics committees and their codes. The title of the talk "sociologically, do we need ethics committees?" began exploring the stigma ethics committee applicants experience when their qualitative research design does not meet the ethics committee's biomedical expectations at issue. In 1992 this disjuncture provoked Tolich's sociological imagination to engage a literature where he found his private troubles were for other sociologists' public issues, as if these other qualitative researchers collectively experienced a similar stigma. The article reports on Tolich's attempts to resolve power imbalances between researchers and ethics committees by creating an experimental ethics committees and resources that support the ethics of social science researchers. The second half of the article critiques the codes ethics committees' use finding they contain little understanding of qualitative research with the potential to harm research participants. The article ends contrasting the impoverishment of New Zealand's ethics codes with those in Australia, and especially in Canada asking why doesn't New Zealand have an equivalent National Statement? [ABSTRACT FROM AUTHOR]

In an influential paper Pesaran ('A simple panel unit root test in presence of cross-section dependence', Journal of Applied Econometrics, Vol. 22, pp. 265-312, 2007) proposes two unit root tests for panels with a common factor structure. These are the CADF and CIPS test statistics, which are amongst the most popular test statistics in the literature. One feature of these statistics is that their limiting distributions are highly non-standard, making for relatively complicated implementation. In this paper, we take this feature as our starting point to develop modified CADF and CIPS test statistics that support standard chi-squared and normal inference. [ABSTRACT FROM AUTHOR]

Official statistics is dipping its toe in the ocean of big data, and leaders are emphasizing the need for a major paradigm change. One aspect is the increased volume of data that are not collected on probability samples of the target population. Making full use of these data requires a fundamental change, not only in data collection and dissemination, but also in the methods of statistical inference. The classical "design-based" approach to survey inference, developed from the seminal work of Neyman [41], is simply not applicable to these data. Rather, statistical models are needed that potentially reflect selection bias from the lack of random sampling. I suggest that "Calibrated Bayes" is the appropriate statistical paradigm for addressing the analysis. Under this paradigm, inferences for a particular data set are Bayesian, but models are sought that yield inferences with robust repeated sampling properties. Probability sampling remains a powerful tool under this paradigm, since by ensuring that the selection mechanism is ignorable it enhances robust modeling, but it is not essential for the inference. I outline two applications of Calibrated Bayes to data collected by the U.S. Census Bureau. [ABSTRACT FROM AUTHOR]

The Survey of Employment, Payrolls and Hours (SEPH) is a monthly business survey conducted by Statistics Canada that produces estimates of levels for variables such as employment, earnings and hours at detailed industrial levels for Canada, the provinces and territories. To improve the efficiency of collection activities for this survey, an electronic questionnaire (EQ) was introduced in the fall of 2012. Given the timeframe allowed for this transition and the production calendar of the survey, a conversion strategy of units from paper questionnaires to EQ was developed. The goal of the strategy was to ensure a good adaptation of the collection environment and also to allow the implementation of a plan of analysis that would evaluate the impact of this change on the results of the survey. This paper will give an overview of the conversion strategy implemented as well as the results of various evaluations that were conducted. For example, the impact of the integration of the EQ on the collection process, the response rate and the failed edit follow-up rate will be presented. In addition, the results of a randomized experiment that was conducted in order to determine the presence of a mode effect will be discussed. [ABSTRACT FROM AUTHOR]

The constant growth of the scope and depth of evidence-based decision making in government throughout the 19th and 20th centuries has led countries to develop the concept of statistical independence of political and other vested interests. This independence is the most important condition necessary for maintaining and increasing data quality, yet the institutional position of statistical offices as part of government makes this hard to achieve. The institutions and governance of statistics in many countries, including developed ones, still leave much to be desired. In spite of this, history of the last several decades suggests there is systematic improvement in the governance of statistics within countries, with legislation and e.g. the acceptance of codes of practice ensuring this independence, etc. Recent developments have, however, introduced a relatively new danger in the rapid development of automatisms, where evidence-based decision making is being replaced by automatic decisions that virtually, or even fully, leave the responsible human decision maker out of the process. This development, which seems to be a welcome gradation of evidence-based decision making, is in fact a grave danger for the independence and quality of statistics, because it re-orients the target of lobbying from the decision makers (who are no longer in the loop) to the data sources, thus putting the quality of official statistics under new powerful pressures. In this context it is more necessary now than ever before to protect the statistical systém from these influences by ensuring full independence in the governance of statistics. [ABSTRACT FROM AUTHOR]

The financial challenges of recent times places a premium on national statistical institutes (NSIs) to creatively examine how to 'do more with less'. Faced with significant staffing reductions and demands for quality improvements, CSO introduced the lean six sigma problem solving methodology. In this paper we explore: * Why CSO introduced lean and how we introduced it * Examples of successful lean projects: how we did it and the benefits achieved in terms of cost reduction and quantifiable quality improvement * Examples of where we had difficulties with lean projects - the learning lessons/implementation issues national statistical institutes should be aware of, including the importance of placing lean within a strategic context. [ABSTRACT FROM AUTHOR]

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This tenth installment of Explorations in Statistics explores the analysis of a potential change in some physiological response. As researchers, we often express absolute change as percent change so we can account for different initial values of the response. But this creates a problem: percent change is really just a ratio, and a ratio is infamous for its ability to mislead. This means we may fail to find a group difference that does exist, or we may find a group difference that does not exist. What kind of an approach to science is that? In contrast, analysis of covariance is versatile: it can accommodate an analysis of the relationship between absolute change and initial value when percent change is useless. [ABSTRACT FROM AUTHOR]

The article presents the compilation of social statistics of the Arab society by the Statistics Division of the Economic and Social Commission for Western Asia region which focuses on the issue of population, education, and poverty.

The rise of the Internet, social media, and digitized historical archives has produced a colossal amount of text-based data in recent years. While computer scientists have produced powerful new tools for automated analyses of such 'big data,' they lack the theoretical direction necessary to extract meaning from them. Meanwhile, cultural sociologists have produced sophisticated theories of the social origins of meaning, but lack the methodological capacity to explore them beyond micro-levels of analysis. I propose a synthesis of these two fields that adjoins conventional qualitative methods and new techniques for automated analysis of large amounts of text in iterative fashion. First, I explain how automated text extraction methods may be used to map the contours of cultural environments. Second, I discuss the potential of automated text-classification methods to classify different types of culture such as frames, schema, or symbolic boundaries. Finally, I explain how these new tools can be combined with conventional qualitative methods to trace the evolution of such cultural elements over time. While my assessment of the integration of big data and cultural sociology is optimistic, my conclusion highlights several challenges in implementing this agenda. These include a lack of information about the social context in which texts are produced, the construction of reliable coding schemes that can be automated algorithmically, and the relatively high entry costs for cultural sociologists who wish to develop the technical expertise currently necessary to work with big data. [ABSTRACT FROM AUTHOR]

Perceived social support is a multifaceted construct conceptualized as one's cognitive appraisal as to the existence of a connection to others, based on trust, on whom one can rely on when necessary. The aim of this paper is to examine the psychometric properties of perceived social support, using the following scales: Social Support Questionnaire-short Form (SSQ6) and Social Provisions Scale (SPS), on a sample of 855 first year university students - 575 females and 280 males - enrolled in 16 professional degrees at the University of Santiago de Compostela (Spain). The SSQ6 Scale assesses the dimensions of perceived support availability and satisfaction, whilst the SPS Scale assesses its social support functions. The factor analysis conducted confirms the SSQ6 Scale's twodimensional model and the SPS Scale's six-factor structure. Internal consistency of both scales is satisfactory, as is the evidence of validity obtained from the correlations between the two scales and their subscales. The results reveal that the Spanish version of the SSQ6 and SPS scales are reliable and valid measurements for assessing perceived social support amongst university students. [ABSTRACT FROM AUTHOR]

The article discusses the relationship between the statistics and sociology in New Zealand considering the International Year of Statistics 2013. Topics include the architecture of New Zealand's official social statistics system such as its goals and structures, the foundation of data-collections, and the use of statistics by the sociological community in New Zealand.

The article offers information on the 42nd Spring Seminar, a training course for social scientists, to be held February 25 until March 15, 2013 in Cologne, Germany, with a particular focus on aspects of statistical modeling with survey data. Topics discussed include details of the lectures given at the seminar by lecturers including Willem E. Saris, Melanie Revilla, and Bruno Arpino.

Copyright of Media4u Magazine is the property of Ing. Jan Chromy, Ph.D. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Futuribles is the property of Futuribles SARL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cahiers Quebecois de Demographie is the property of Association des Demographes du Quebec and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Pierre Bourdieu's recasting of the question of class exemplifies the major features of his sociology and the way he extends, melds and mends classical views into a distinctive framework. Bourdieu's approach is relational, agonistic, and synthetic; it spotlights the symbolic dimension of group formation as practical achievement while fusing theory and research; and it introduces multiple correspondance analysis as a statistical technique suited to grasping constellations of multiple capitals. Bourdieu reformulates the problem of domination by questioning the ontological status of collectives and by forging tools for elucidating the politics of group-making: the sociosymbolic alchemy where- by a mental construct is turned into a historical reality through the inculcation of schemata of perception and their deployment to draw, enforce, or contest social boundaries. The article traces the impetus behind the key conceptual shifts Bourdieu effects, from class structure to social space, from class consciousness to habitus, from ideology to symbolic violence, and from ruling class to field of power. It also points to recent studies that have tried, tested, and refined the core tenets of his model as well as offers a bibliography of Bourdieu's publications on class documenting a twofold empirical and analytic shift towards a sociology of the realization of categories that spotlights the constitutive power of symbolic structures. [ABSTRACT FROM AUTHOR]

Lesbian, gay, bisexual, transgender, and queer (LGBTQ) individuals have increased vulnerability for a number of negative outcomes in comparison to heterosexual peers. Sexual minorities in rural areas have increased vulnerability beyond what is experienced by urban peers. Protective factors have been identified that may insulate individuals from vulnerabilities. Using a sample of 69 participants, an ANOVA was conducted to determine the relationship between identified protective factors and sexual orientation. Findings indicated that bisexual individuals were less likely to see social support as helpful in comparison to gay, lesbian, or heterosexual participants. A discussion of how the findings may impact the transition to college is provided. [ABSTRACT FROM AUTHOR]

Copyright of BMS: Bulletin de Methodologie Sociologique (Sage Publications Ltd.) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: This paper presents the results of an innovative use of the Delphi technique to obtain quantitative information for the evaluation of the Official Adjustment Rules for Damage Assessment in agricultural insurance. An efficient insurance system must guarantee that loss adjustment is performed fairly and transparently, so that the continual review and modification of adjustment rules becomes especially important. The present study develops and applies a methodology based on the subjective information compiled by experts to evaluate the modification of the Specific Loss Adjustment Rule for Fruit Crops under real market conditions. The results show that the method employed comes forward as a valid option to provide reliable information, as well as other economic and social advantages, in the absence of alternative statistical sources. The validity of the study has been proved by its utility, as the results were extremely useful for drawing up a new Official Adjustment Rule. This application opens up an interesting field of development for this technique, which will enable the proposed methodology to be applied to similar studies in the context of agricultural insurance loss adjustment. [Copyright &y& Elsevier]

This article reports on a sociology research method called "Propensity Score Matching," which is a method used in order to get an unbiased statistical analysis of observational data. Several topics are discussed, including that with sociological research data it is hard to differentiate between certain characteristics, how Propensity Score Matching (PSM) can help with this issue because it is able to determine causal inferences, and how with PSM the variables being studied are randomized, which causes any sort of systematic differences between the groups being researched to be eliminated. The article also provides a step-by-step guide to doing an analysis using PSM, and discusses what type of research it the method is best suited for.

We examine several approaches for inferring logit models from empirical margins of predictor covariates and conditional margins containing the means of a binary response for each covariate margin. One method is to fit proxy data to the conditional response using the beta distribution, a process we call 'margin analysis.' Proxy data can obtained using three approaches: (1) implementing the iterative proportional fitting (IPF) procedure on the margin totals, (2) sampling from a larger relevant data source such as the census, and (3) enumerating, or sampling from, the combinatoric space of all possible tables constrained by the margins. The first procedure is a well-studied approach for estimating contingency tables from margins, but it does not necessarily maintain the associations between the covariates unless seeded with an initial table containing those associations. In the second approach, which is appropriate for analyzing sociodemographic covariates, we can use a large census sample adjusting for sampling biases observed in the empirical margins. However, the appropriateness of using a census proxy depends substantially on how similar the sampling pools are. Our third approach entails exploring the combinatoric space of all contingency tables constrained by the margins while considering the associations among the covariates. We aggregate the logit models estimated from each table in that space into a single model. This approach is more robust than the first two as it considers multiple proxies. While the estimated logit models from each approach are generally similar to one another, for the low-dimensional tables we explore in this paper, the combinatoric approach incurs wider standard errors, which renders potentially significant coefficients insignificant. Finally, we suggest weighting the combinatoric models with evidence-relevant probabilities obtained using the multivariate Pólya distribution. [ABSTRACT FROM AUTHOR]

The author offers a response to the articles "Snowball Sampling," published in a 1961 issue of "Annals of Mathematical Statistics," and "Respondent-Driven Sampling: An Assessment of Current Methodology," published in a 2010 issue of the publication. It is stated that snowball sampling in populations difficult to reach for research purposes is not the same as response-driven sampling but, the two methods can be combined for conducting research on such groups.

Many basic questions in the social network literature center on the distribution of aggregate structural properties within and across populations of networks. Such questions are of increasing relevance given the growing availability of network data suitable for meta-analytic studies, as well as the rise of study designs that involve the collection of data on multiple networks drawn from a larger population. Despite this, little work has been done on model-based inference for the properties of graph populations, or on methods for comparing such populations. Here, we attempt to rectify this gap by introducing a family of techniques that combines an existing approach to the identification of structural biases in network data (the use of conditional uniform graph quantiles) with strategies drawn from nonparametric Bayesian analysis. Conditional uniform graph quantiles are the quantiles of an observed structural property in the reference distribution produced by evaluating that property over all graphs with certain fixed characteristics (e.g., size or density). These quantiles have long been used to measure the extent to which a property of interest on a single network deviates from what would be expected given that network's other characteristics. The methods introduced here employ such quantile information to allow for principled inference regarding the distribution of structural biases within (and comparison across) populations of networks, given data sampled at the network level. The data requirements of these methods are minimal, thus making them well-suited to meta-analytic applications for which complete network data (as opposed to summary statistics) are often unavailable. The structural biases inferred using these methods can be expressed in terms of posterior predictives for familiar and easily communicated quantities, such as p-values. In addition to the methods themselves, we present algorithms for posterior simulation from this model class, illustrating their use with applications to the analysis of social structure within urban communes and radio communications among emergency personnel. We also discuss how this approach may applied to quantiles arising from other reference distributions, such as those obtained using general exponential-family random graph models. [ABSTRACT FROM AUTHOR]

The author offers opinions on the article "On Respondent-Driven Sampling and Snowball Sampling in Hard to Reach Populations and Snowball Sampling not in Hard-to-Reach Populations," by Leo A. Goodman, published in this issue. It is stated that confusion between snowball sampling as a methodology in statistics and respondent-driven sampling RDS) stems from multiple forms of the estimator in the RDS process stemming from the incremental development of the methodology.

Recent research has shown that two entropy-based segregation indices possess an appealing mixture of basic and subsidiary but useful properties. It would appear that the only fundamental difference between the mutual information or M index, and the entropy information or H index, is that the second is a normalized version of the first. This paper introduces another normalized index in that family, the H* index, which captures segregation as the tendency of racial groups to have different distributions across schools. More importantly, the paper shows that applied researchers may do better using the M index than using either H or H* in two circumstances: (1) if they are interested in the decomposability of the measurement of segregation, and (2) if they are interested in a margin-free measurement of segregation changes. The shortcomings of the H and H* indices are illustrated below by means of numerical examples, as well as with school segregation data by ethnic group in the U.S. public school system between 1989 and 2005. [ABSTRACT FROM AUTHOR]

An introductions is presented to articles published in this issue including "How Not to Lie With Ethnography," "Inferring Logit Models from Emplrical Margins Using Proxy Data" and "Entropy-Based Segregation Indices."

The author offers opinions on the article "On Respondent-Driven Sampling and Snowball Sampling in Hard to Reach Populations and Snowball Sampling not in Hard-to-Reach Populations," by Leo A. Goodman, published in this issue. It is stated that the term snowball sampling has come to refer to two different means of conducting sampling in sociology research, obscuring the use of respondent-driven sampling which is seen as superior methodology when studying hard to reach populations.

General random graphs (i.e., stochastic models for networks incorporating heterogeneity and/or dependence among edges) are increasingly in wide use in the study of social and other networks, but few techniques other than simulation have been available for studying their behavior. On the other hand, random graphs with independent edges (i.e., the Bernoulli graphs) are well-studied, and a large literature exists regarding their properties. In this paper, we demonstrate a method for leveraging this knowledge by constructing families of Bernoulli graphs that bound the behavior of an arbitrary random graph in a well-defined sense. By studying the behavior of these Bernoulli graph bounds, we can thus constrain the properties of a given random graph. We illustrate the utility of this approach via application to several problems from the social network literature, including identifying degeneracy in Markov graph models, studying the potential impact of tie formation mechanisms on epidemic potential in sexual contact networks, and robustness testing of inhomogeneous Bernoulli models based on geographical covariates. Practical heuristics for assessing bound tightness and guidance for use in theoretical and methodological applications are also discussed. [ABSTRACT FROM AUTHOR]

The theoretical consequences of measurement error in outcome variables that are continuous are widely known by practitioners, at least for the classical model: purely random errors will lead to a loss of efficiency but not to bias in regression coefficients. When the outcome variable is binary, however, regression coefficients, both linear and nonlinear, will contain bias, even if the measurement error (in this setting more commonly referred to as classification error) is purely random. This paper illustrates a method of correcting for misclassification bias that relies solely on the primary survey data. It is particularly suited to analyses of surveys where external validation of survey responses is unavailable but where there is strong reason to suspect contaminated data. This situation is common in observational studies of the health of populations. The technique is applied to a model of the antecedents of post-traumatic stress disorder (PTSD) using data from a large-scale cross-sectional survey of Vietnam-era veterans. Results show that when adjusted for errors in diagnoses, the sample PTSD prevalence estimate falls significantly; that failure to correct for misclassification in PTSD dramatically understates the effects of risk factors; and that this downward bias remains even when the model incorporates differential classification errors-that is, errors that are correlated with some of the explanatory variables in the model. [ABSTRACT FROM AUTHOR]

Conceptions of well-being are cognitive representations of the nature and experience of well-being. These conceptions can be described generally by the degree to which hedonic and eudaimonic dimensions are emphasized as important aspects of the experience of well-being. In two studies, the prediction that eudaimonic dimensions of individual conceptions of well-being are more robustly associated with self-reported well-being than hedonic dimensions was investigated. Correlational analyses indicated that both hedonic and eudaimonic dimensions were associated with well-being, with more robust associations observed between the eudaimonic dimension and each measure of well-being. In several regression analyses, only the eudaimonic dimension significantly predicted well-being, with the hedonic dimension failing to account for unique variance in well-being beyond that predicted by the eudaimonic dimension. Results thus generally suggest that conceptualizing well-being in eudaimonic terms may be relatively more important for positive psychological functioning. [ABSTRACT FROM AUTHOR]

In this paper we present a new global evaluation methodology for constructing composite indicators. Given the limitations in the construction of wellbeing indicators that include a gender perspective, this paper proposes separate measures for men and women, using new linear programming models to improve the traditional Data Envelopment Analysis models. We obtain composite indicators using common weights (which are most and least favourable) so that the indicators' values are able to discriminate between all units and provide a global vision of each one. This approach does not require prior knowledge of the weights for initial indicators, nor does it require a normalization method. Thus, the new composite indicator is less subjective than others. For the practical implementation of this proposal, we use the countries of the European Union as an example. [ABSTRACT FROM AUTHOR]

Few studies have examined how financial relationship issues are associated with cohabiting individuals' risk of union dissolution or marriage. Competing-risks Cox regressions using the cohabiting data in the National Survey of Families and Households (N = 483) found that financial disagreements predicted union dissolution, whereas disagreements about housework, spending time together, sex, and parents did not. Perceived unfairness in finances also predicted union dissolution. Although perceived housework unfairness also positively predicted dissolution, this effect was moderated by gender. Interestingly, neither financial issues nor the other normative problems predicted the likelihood of marriage. These findings suggest that the relationship problems associated with financial issues are particularly salient to cohabiting individuals' decision to end their unions. [ABSTRACT FROM AUTHOR]

The article describes an alternative approach of gathering in-depth qualitative accounts and content coding them for statistical analysis, wherein the regression coefficients of workplace ethnographies were introduced into a body of sociological research. It is attested that the merging of qualitative and quantitative approaches in sociology is advancing through methods such as appending comprehensive interviews to surveys. It is further posited that funding requirements for such projects are minimal and students can easily be involved. The authors conclude by discussing other bodies of ethnographic research that are ready for systematic analysis.

This study of characterization of higher and distance education in Colombian universities presents the current status of distance education. While we have statistical studies on higher education, they are not specific on distance education, notwithstanding the fact that it represents 10% of higher education in our country. The main source of information is the analysis and exploration of the data provided by the National Higher Education Information (SNIES) and the Labor Observatory for Education, official information systems from the Ministry of Education, which provide extensive statistical information about higher education in Colombia. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we employ, and test the reliability and validity, of multiple corruption related datasets such as the Corruption Perceptions Index of Transparency International, the Control of Corruption Index of the World Bank, the International Country Risk Guide of PRS, the World Value Survey, the Bribe Payers Index, and the International Crime Victimization Survey. We find evidence that the reliability of international corruption indexes has improved over the years. However, a number of shortcomings – such as the risk of selection bias, longitudinal sensitivity, and measurement errors that are inherent in composite indexes – are commonly observed. These problems are critical enough to affect the results of empirical analysis, as we illustrate using linear models. Therefore, we conclude that researchers should pay more attention towards minimizing the impact of measurement error through rigorous data screening and robustness tests using multiple data sources and methods. A thorough and systematic evaluation of the reliability and validity of international corruption indexes is essential to increase their usefulness. [Copyright &y& Elsevier]

Respondent-driven sampling (RDS) employs a variant of a link-tracing network sampling strategy to collect data from hard-to-reach populations. By tracing the links in the underlying social network, the process exploits the social structure to expand the sample and reduce its dependence on the initial (convenience) sample. The current estimators of population averages make strong assumptions in order to treat the data as a probability sample. We evaluate three critical sensitivities of the estimators: (1) to bias induced by the initial sample, (2) to uncontrollable features of respondent behavior, and (3) to the without-replacement structure of sampling. Our analysis indicates: (1) that the convenience sample of seeds can induce bias, and the number of sample waves typically used in RDS is likely insufficient for the type of nodal mixing required to obtain the reputed asymptotic unbiasedness; (2) that preferential referral behavior by respondents leads to bias; (3) that when a substantial fraction of the target population is sampled the current estimators can have substantial bias. This paper sounds a cautionary note for the users of RDS. While current RDS methodology is powerful and clever, the favorable statistical properties claimed for the current estimates are shown to be heavily dependent on often unrealistic assumptions. We recommend ways to improve the methodology. [ABSTRACT FROM AUTHOR]

This paper proposes a two-stage maximum likelihood (ML) approach to normal mixture structural equation modeling (SEM) and develops a statistical inference that allows distributional misspecification. Saturated means and covariances are estimated at stage 1 together with a sandwich-type covariance matrix. These are used to evaluate structural models at stage 2. Techniques accumulated in the conventional SEM literature for model diagnosis and evaluation can be used to study the model structure for each component. Examples show that the two-stage ML approach leads to correct or nearly correct models even when the normal mixture assumptions are violated and initial models are misspecified. Compared to single-stage ML, two-stage ML avoids the confounding effect of model specification and the number of components, and it is computationally more efficient. Monte Carlo results indicate that two-stage ML loses only minimal efficiency under the condition where single-stage ML performs best. Monte Carlo results also indicate that the commonly used model selection criterion BIC is more robust to distribution violations for the saturated model than that for a structural model at moderate sample sizes. The proposed two-stage ML approach is also extremely flexible in modeling different components with different models. Potential new developments in the mixture modeling literature can be easily adapted to study issues with normal mixture SEM. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to generate discussion about the teaching and learning sociology and religious studies using the "study in depth" method. In addition, the author shares with readers how one course, and a specific set of readings contributed to a department's overall plan for study in depth in sociology. Study in depth is defined as the comprehension of "a complex structure of knowledge" (Association of American Colleges). It uses a multidisciplinary approach that is vital to teaching and learning sociology, religious studies, and other subjects. Sociology of Religion at this university is an upper-division elective for sociology majors and minors, religious studies minors (there is no religious studies major), and general studies majors (concentration in culture and society; and in religious studies). Introduction to Sociology is a prerequisite for Sociology of Religion. Since this course is not required, the majority of students who enroll in it do so because they have a genuine interest in it. Monographs can be incorporated into a variety of social science and religious studies courses to facilitate study in depth. The use of research monographs can foster deep learning and enable students to become highly informed learners who are capable of critical thinking. [ABSTRACT FROM AUTHOR]