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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]

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]

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.)

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.

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]

Copyright of BMS: Bulletin de Méthodologie Sociologique (l'Association Internationale de Méthodologie Sociologique (AIMS)) is the property of l'Association Internationale de Methodologie Sociologique (AIMS) 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.)

Arguably, sociologists often apply deterministic explanations, unlike in many other sciences where probabilistic explanations have turned out to be more efficient. The advantages of applying probabilistic explanations more frequently could be: improved possibilities for cross-disciplinary work; the simplification of successful explanations; an easier way to implement uncertainty to models; new ways to utilize the classical theories of sociology; and increased freedom to choose research methods. According to the previously published literature, one of the reasons for not applying probabilistic explanations has been the strong positivist heritage in sociology. The following additional factors are considered: important classics of sociology were written before probability theories matured; and qualitative methods have provided the possibility to respond to the need for empirical research. In this way, sociologists have avoided the extensive work of re-evaluating the existing theories from a probabilistic point of view. [ABSTRACT FROM AUTHOR]

The article presents a research response to the methodological criticism issued by Tom Van der Meer, Manfred Te Grotenhuis, and Ben Pelzer included within the issue, challenging the case examples provided in the author's sociological analysis of religiosity and volunteering behavior in the United States. The authors disagree with the conclusions made against their original study but also compliment the methodology suggestions raised by the article and provide alternative paradigms for future studies to correct for the problems.

The article discusses the statistical approach to ethnic and racial social relations in France. It explores social scientists' development of strategies on proxies for ethnic and racial categories. Variables such as names, nationality, and language spoken at home are suggested to allow for building categories that are not significantly remote from ethnic ones. The alleged duty of the social sciences to objectify groups that start denouncing what they consider to be discrimination is also examined.

The article discusses issues relating to the scientific and political aspects of ethnic categories in France's official statistics as well as practical problems involved in the use of such categories. It examines how the refusal to create religious and ethnic categories is partly related to the French sociological tradition. The difficulty of seeing how ethnic categories could be built for use in public statistics in a disinterested and impartial way is explored. The author argues that ethnic statistics run counter to the French integration tradition.

To study life course trajectories and ageing, scientific expertise is needed beyond epidemiology. More specifically, appropriate models of life course require a theoretical micro-foundation, need to incorporate multi-level context conditions and the interplay between them. It also requires the application of additional social scientific research methods that go beyond the application of statistical methods based on the multi-stage life table. These research theories and methods are available in disciplines like sociology, cultural anthropology, psychology, demography and economics. To effectively study healthy ageing of populations the individual approach of epidemiology has to be extended with the macro-population and socio-cultural approach of (social) demography and the institutional and network approaches of sociology. [ABSTRACT FROM AUTHOR]

Purpose - This paper aims to tackle in turn the merits and limits of Nicholas Georgescu-Roegen's entropic model, as well as its implications for the methodological discourse in economics. This appraisal of the Georgescu-Roegen's work emphasizes the emergence of the entropic nature of the economic processes as a paradigm a la Kuhn of explanation in social economics. Design/methodology/approach - This work provides a critical assessment of the entropic model's main conceptual pillars, namely the role of mathematical formalism and the natural imagery of irreversifrility. This discussion takes them in turn and develops a critique from a methodological point of view. Findings - The focus of this work is that the proposed epistemological reconstruction of economics is vulnerable to attacks from two methodological objections. The first deals with the change of metaphor from the "pendulum" of mechanics to the "hourglass" of thermodynamics. The second refers to the changes this replacement of metaphors brings about as to the relevance of the formalism of the discipline. Originality/value - This material has gathered arguments to show that the intellectual concurrence of the arguments onto the field of physics makes the methodological value of the new paradigm of entropy not transcend into a new logic of reasoning in economics. The limits of this approach stems from the same rationale for which it has got its revolutionary stature: what it proposes consists of a scientific discourse based on a mixture of evolutionary biology, economics and thermodynamics, which may open up new original and insightful perspectives, but which has never been justified on terms of economic nature alone. [ABSTRACT FROM AUTHOR]

The article reviews several periodicals including "La revue française de sociologie," "L'Année sociologique" and "The Journal of Official Statistics."

Copyright of BMS: Bulletin de Méthodologie Sociologique (l'Association Internationale de Méthodologie Sociologique (AIMS)) is the property of l'Association Internationale de Methodologie Sociologique (AIMS) 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 BMS: Bulletin de Méthodologie Sociologique (l'Association Internationale de Méthodologie Sociologique (AIMS)) is the property of l'Association Internationale de Methodologie Sociologique (AIMS) 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 BMS: Bulletin de Méthodologie Sociologique (l'Association Internationale de Méthodologie Sociologique (AIMS)) is the property of l'Association Internationale de Methodologie Sociologique (AIMS) 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 BMS: Bulletin de Méthodologie Sociologique (l'Association Internationale de Méthodologie Sociologique (AIMS)) is the property of l'Association Internationale de Methodologie Sociologique (AIMS) 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.)

This paper describes and contrasts two useful ways to employ a latent class variable as a mixture variable in regression analyses of panel data with a categorical dependent variable. One way is to model unobserved heterogeneity in the trajectory, or change in the distribution, of the dependent variable. Two models that accomplish this are the latent trajectory model and latent growth curve model for a categorical dependent variable having ordered categories. Each latent class here represents a distinct trajectory of the dependent variable. The latent trajectory model introduces covariate effects on the composition of latent classes, while the latent growth curve model introduces covariate effects on both the “intercept” and the “slope” of growth in logit, which may vary among latent classes. The other useful way is to model unobserved heterogeneity in the state dependence of the dependent variable. Two models that accomplish this are introduced for a simultaneous analysis of response probability and response stability, and the latent class variable is employed to distinguish two latent populations that differ in the stability of responses over time. One of them is the switching multinomial logit model with a time-lagged dependent variable as its separation indicator, and the other is the mover-stayer regression model. By applying these four models to empirical data, this paper demonstrates the usefulness of these models for panel-data analyses. Example programs for specifying these models based on the LEM program are also provided. [ABSTRACT FROM AUTHOR]

This article questions whether implication analysis, an approach to statistical sociology described by Stanley Lieberson and Joel Horwich elsewhere in this journal, is a novel approach to sociology. The author reframes Lieberson and Horwich's criticism of statistical methods in sociology as a condemnation of scholarly research based on weak data. Questions are also raised about the use of science as an example for sociology. The author suggests that an investigation of the relationship between experimental psychology and predictive approaches to sociology could improve the credibility of that field.

This article discusses the questions about experimental design raised by Stanley Lieberson and Joel Horwich elsewhere in this issue. Lieberson and Horwich advanced the theory of implication analysis as an alternative to experimental designs in sociology that prioritize falsifiability. The potential contribution of implication analysis to the design of statistical regression models in sociological research is described. Questions are raised about how the fairness of the Lieberson and Horwich's analysis of scientific thought as it relates to sociological analysis. Implication analysis is considered in terms how its application would change the emphasis given to control variables and alternative theories in the development of sociological research.

This article responds to an article on the design of sociological experiments written by Stanley Lieberson and Joel Horwich and published elsewhere in this journal. The weighting of evidence in the testing of sociological hypotheses is addressed. Dichotomies between induction and deduction in the analysis of sociological data are criticized in favor of abductive methods in sociological research. The design of an experiment intended to determine whether chemical and biological weapons were used in conflicts in Laos, Cambodia, and Afghanistan during the 1970s is considered.

This article responds to the development of implication analysis, an approach to sociological research that emphasizes thorough analysis of the theoretical context within which data are analysed. This approach is developed in an essay by Joel Horwich and Stanley Lieberson elsewhere in this issue. The application of Horwich and Lieberson's approach to the construction of doctoral dissertations is framed in terms of the limitations that it would place on the creativity of students. Issues relating to the generation of comparative data to carry out the projects of implication analysis are considered.

This article looks at the history of statistics concerning race relations in the United States. The terminology used in this discussion is presented which includes white, black, Asian, American Indian, Pacific Islander, and other. The political considerations of these figures are also examined. Several questions are explored including whether these terms benefit those that they describe. The authors attempt to discover the politics behind these statistics as they argue that none of the figures are neutral but always provide a bias. However, they also propose that they have effected positive results in racial and ethnic discrimination in the United States.

The increase in life expectancy at middle age has added quality of life to the policy concerns related to older ages. The present article asks whether this quality of life varies with socio-economic position. Using data from the English Longitudinal Study of Ageing (n.d.), the article answers this question in terms of the National Statistics Socio-Economic Classification and CASP-19, a measure of positive quality of life in early old age. Among all respondents aged 50 to 75 years, quality of life was found to be graded by social position, with the difference in quality of life between the higher managerial and professional group and the routine group being of comparable size to having a limiting long-standing illness; with the size of this difference varying between labour market sub-groups. The implication of these findings for ageing policy and for the National Statistics Socio-Economic Classification are discussed. [ABSTRACT FROM AUTHOR]

This article examines more carefully the oft-made hypotheses that (1) ‘technocrats’ or politicians with an economics background are increasingly common and (2) that this ‘improvement’ in qualifications will lead to improvements in economic policy. The article presents a database on the qualifications of leaders of the world's major countries over the past four decades. The article finds that while there is evidence for increasing ‘technification,’ there are also distinct and persistent historical patterns among Asian, African, Middle Eastern, and Latin American leaders. Using statistical analysis, the article finds that we cannot conclude that leadership training in economics leads to better economic outcomes. [ABSTRACT FROM AUTHOR]

Objective. We sought to examine the relation between physical activity and incident hypertension in young adults over 15 years of follow-up in the Coronary Artery Risk Development in Young Adults study. Methods. A total of 3993 Black and White men and women aged 18 to 30 years were examined at baseline, and 2, 5, 7, 10, and 15 years later. Blood pressure and physical activity were measured at each exam. Hypertension was defined as systolic 140 mm Hg or higher, diastolic 90 mm Hg or higher, or antihypertensive medication use. Average physical activity and incident hypertension over 15 years of follow-up were analyzed. Results. There were 634 cases of incident hypertension over 15 years of follow-up. Those who were more versus less physically active experienced a reduced risk (hazard rate ratio =0.83; 95% confidence interval = 0.73, 0.93) for incident hypertension, after adjustment for race, sex, age, education, and family history of high blood pressure. Conclusions. Physical activity merits attention in the prevention of incident hypertension among young adults, particularly as they move into middle age. (Am J Public Health. 2007;97:703-709.) [ABSTRACT FROM AUTHOR]

The American Community Survey (ACS), designed to take the place of the decennial census long-form survey, has begun. The first data products from the full-implementation ACS were released in August 2006 for areas with populations of 65,000 or more in the U.S. and Puerto Rico, where the program is called the Puerto Rico Community Survey (PRCS). What is the status of the program? What kinds of data are available now, and how are the data being used? Here is a glimpse of where the program stands in early 2007. [ABSTRACT FROM AUTHOR]

This article presents information on the life of sociologist Frédéric Le Play, and discusses various issues related to his contributions to the field of sociology. Le Play, who also worked as a mining engineer, occupies a prominent place in the field of sociology. His professional activities enriched him intellectually. He is a key figure to understand the process of creation of sociology. He had developed his own method for the study of society which is based on monographs of working families. He advocated for having a science of the government wherein planning is based on statistical evidences. According to Le Play, statistics must be in hands of those who have the means of observation--the government and not the particular affiliations.

The most promising class of statistical models for expressing structural properties of social networks observed at one moment in time is the class of exponential random graph models (ERGMs), also known as p* models. The strong point of these models is that they can represent a variety of structural tendencies, such as transitivity, that define complicated dependence patterns not easily modeled by more basic probability models. Recently, Markov chain Monte Carlo (MCMC) algorithms have been developed that produce approximate maximum likelihood estimators. Applying these models in their traditional specification to observed network data often has led to problems, however, which can be traced back to the fact that important parts of the parameter space correspond to nearly degenerate distributions, which may lead to convergence problems of estimation algorithms, and a poor fit to empirical data. This paper proposes new specifications of exponential random graph models. These specifications represent structural properties such as transitivity and heterogeneity of degrees by more complicated graph statistics than the traditional star and triangle counts. Three kinds of statistics are proposed: geometrically weighted degree distributions, alternating k-triangles, and alternating independent two-paths. Examples are presented both of modeling graphs and digraphs, in which the new specifications lead to much better results than the earlier existing specifications of the ERGM. It is concluded that the new specifications increase the range and applicability of the ERGM as a tool for the statistical analysis of social networks. INSETS: Figure 1: Some configurations for nondirected graphs.;Figure 2: Partial conditional dependence when four-cycle...;Figure 3: Two examples of a two-triangle.;Figure 4: A k-triangle for k=5; also called a five-triangle [ABSTRACT FROM AUTHOR]

The article presents information on several books, journals and reports related to research in social sciences. The special issue of the "Journal of Mathematical Sociology," is based on the theme "The Emergence of Social Order." The contents of this issue include "Introduction: The Question of the Origins," "Change in the Form of Evolution. Transition From Primate to Hominid Forms of Social Organization," "Knowledge Learning and Social Swarms in Cultural Systems," and others. The December 2005 issue of the "International Journal of Social Research Methodology," focuses on quantitative and qualitative research methodologies. The volume 26 of "Connections," the journal of the International Network of Social Network Analysts focuses on various topics related to social network analysis, and is now available on the Web site, http://www.insna.org/Connections-Web/.

The article presents a teaching technique designed to motivate students to learn statistics. The author gives students a list of common occupations for people with a degree in Sociology, their salaries, and the use of statistics in the occupation. The goals of this technique is to convince students that statistics is a worthwhile subject to learn, to reduce student anxiety by letting them demonstrate that they can do statistics, and to provide an example that can be used throughout the semester to illustrate multiple statistical techniques. The approach simply acknowledges that money matters to students. It uses the promise of monetary reward to give them at least one reason to pay attention and learn throughout the rest of the course.

Focuses on the response to the previous review essay of three statistics textbooks in the field. Assessment of the basis of the review; Emphasis to study on statistical theory rather than the application of the theory; Aim to deal with theory in mathematical terms.

The article presents information on the Spring 2005 newsletter of the International Sociological Association's RC33 Research Committee. The RC33 has invited papers which are to be presented at the World Congress of Sociology in Durban, South Africa, in July 2006. An evaluation of the RC33 Sixth International Conference on Social Science Methodology, "Recent Developments and Applications in Social Research Methodology," which was held in Amsterdam, the Netherlands, from August 17-20, 2004, is also presented. The conference included 500 papers in 54 sessions and there were 575 participants from more than 20 countries. Keynote speakers Lyn Richards and David Cox presented their lectures titled "Qualitative Software and Methodological Change: Myths, Mindsets and Methodological Mania," and "Current Challenges for Statistical Science," respectively.

Focuses on the distributional models between national and world society. Description of bell curve model; Proposals made by Durkheim and Mauss on the forms of social origin; Link of the discovery of power laws to the physics of complexity.

This article discusses the use of concrete historical examples to enhance learning in statistics classes. A host of scholars have acknowledged the difficulties experienced by students learning research methods and statistics, especially those in the social sciences who may not be as mathematically inclined as students in other fields of study. Students' anxieties may cause them to delay taking methods courses, adversely affecting their ability to understand material in other classes that incorporate these tools. Many suggestions for easing student anxiety have been offered, including the use of humor, small group work, and use of local county data. Some students never seemed to get over their anxiety about statistics. Students occasionally returned a year or two later to ask questions that indicated that they had not retained, at least with any confidence, the material they had learned in the classroom. Two approaches were developed to deal with these concerns of learning and retention. First, instead of reliance upon lecture notes per se, the plan of instruction instead incorporated data analysis learning objectives. The second instructional approach included finding and applying examples that would meet several criteria for sustaining student interest and enhancing their learning and confidence with statistics.

Recent developments in mathematical demography offer a new, simple means of producing long-range population projections. The well-known extant such projections, produced by the United Nations, the World Bank, and the International Institute for Applied Systems Analysis, rely on elaborate cohort-component projection methods that require a large number of detailed assumptions and are difficult to replicate. Building upon recent results in the formal demography of nonstable populations, the authors show that analytic methods produce estimates of future population size very similar to those obtained through traditional methods. Simplicity is a virtue in making projections, allowing sensitivity tests of assumptions and avoiding the misleading impression of precision associated with more complicated methods. Cohort-component methods should still be used for short- and medium-term forecasts and projections. For the long term, however, analytic methods should supplement or even replace traditional projections. [ABSTRACT FROM AUTHOR]