关于新时期西北少数民族题材绘画创作的反思

西北少数民族题材绘画为建构中国现代美术形态起一定的作用,但同时自身存在许多负面因素值得我们思考。本文着重从题材表现手法的模式化、作品内涵的表面化及表现形式的局限性、与现代绘画艺术的冲突这几方面展开分析。     

Latent class analysis of response inconsistencies across modes of data collection

Latent class analysis (LCA) has been hailed as a promising technique for studying measurement errors in surveys, because the models produce estimates of the error rates associated with a given question. Still, the issue arises as to how accurate these error estimates are and under what circumstances they can be relied on. Skeptics argue that latent class models can understate the true error rates and at least one paper (Kreuter et al., 2008) demonstrates such underestimation empirically. We applied latent class models to data from two waves of the National Survey of Family Growth (NSFG), focusing on a pair of similar items about abortion that are administered under different modes of data collection. The first item is administered by computer-assisted personal interviewing (CAPI); the second, by audio computer-assisted self-interviewing (ACASI). Evidence shows that abortions are underreported in the NSFG and the conventional wisdom is that ACASI item yields fewer false negatives than the CAPI item. To evaluate these items, we made assumptions about the error rates within various subgroups of the population; these assumptions were needed to achieve an identifiable LCA model. Because there are external data available on the actual prevalence of abortion (by subgroup), we were able to form subgroups for which the identifying restrictions were likely to be (approximately) met and other subgroups for which the assumptions were likely to be violated. We also ran more complex models that took potential heterogeneity within subgroups into account. Most of the models yielded implausibly low error rates, supporting the argument that, under specific conditions, LCA models underestimate the error rates.     

Confidence regions for two proportions from independent negative binomial distributions

The negative binomial distribution offers an alternative view to the binomial distribution for modeling count data. This alternative view is particularly useful when the probability of success is very small, because, unlike the fixed sampling scheme of the binomial distribution, the inverse sampling approach allows one to collect enough data in order to adequately estimate the proportion of success. However, despite work that has been done on the joint estimation of two binomial proportions from independent samples, there is little, if any, similar work for negative binomial proportions. In this paper, we construct and investigate three confidence regions for two negative binomial proportions based on three statistics: the Wald (W), score (S) and likelihood ratio (LR) statistics. For large-to-moderate sample sizes, this paper finds that all three regions have good coverage properties, with comparable average areas for large sample sizes but with the S method producing the smaller regions for moderate sample sizes. In the small sample case, the LR method has good coverage properties, but often at the expense of comparatively larger areas. Finally, we apply these three regions to some real data for the joint estimation of liver damage rates in patients taking one of two drugs.     

Multivariate generalized Birnbaum—Saunders kernel density estimators

In this article, we first propose the classical multivariate generalized Birnbaum–Saunders kernel estimator for probability density function estimation in the context of multivariate non negative data. Then, we apply two multiplicative bias correction (MBC) techniques for multivariate kernel density estimator. Some properties (bias, variance, and mean integrated squared error) of the corresponding estimators are also investigated. Finally, the performances of the classical and MBC estimators based on family of generalized Birnbaum–Saunders kernels are illustrated by a simulation study.     

Estimation of zero-inflated parameter-driven models via data cloning

ABSTRACT

In this paper, we propose the use of the Data Cloning (DC) approach to estimate parameter-driven zero-inflated Poisson and Negative Binomial models for time series of counts. The data cloning algorithm obtains the familiar maximum likelihood estimators and their standard errors via a fully Bayesian estimation. This provides some computational ease as well as inferential tools such as confidence intervals and diagnostic methods which, otherwise, are not readily available for parameter-driven models. To illustrate the performance of the proposed method, we use Monte Carlo Simulations and real data on asthma-related emergency department visits in the Canadian province of Ontario.     

AIDS:

No abstract available for this article.     

Daily work events and state work engagement: the mediating role of affect / Eventos diarios y work engagement: el rol mediador del afecto

Abstract

According to Affective Events Theory, the emotional elicitation process is initiated by the appraisal of affective events happening to employees. Moreover, the theory states that these elicited affective experiences influence attitude and behaviour in the workplace. In the present study this theoretical frame is applied to explain the interplay of variables influencing state work engagement. We analyse the mediating role of affect between work events’ appraisals and daily work engagement, using a diary study. One hundred and seventeen workers answered a daily questionnaire for at least 10 days generating a total of 1,203 registers. Multilevel analysis proved that daily events’ appraisal is positively related to state work engagement, and that this relationship is partially mediated by positive and negative affect. Moreover, the effect of positive affect was bigger than the one of negative affect. The explored relations provide new theoretical elements for models that explain which variables influence state work engagement.     

From the Trenches: Attacking First-Time Women Candidates for Congress

SUMMARY

Women candidates in the United States no longer enjoy a “compassion advantage” when running against male candidates. First-time women congressional candidates in open seats are especially vulnerable to excessively aggressive negative attacks from their male opponents because (1) high-tech message delivery systems make attack campaigning easy; (2) attack messages attract more attention than positive messages and get the voters to pay attention; (3) large sums of money can be raised for these attacks from national interest groups by emphasizing the national importance of Congressional races; (4) first-time women candidates who are not elected officials do not have the public record and visibility that could insulate them from the abusive distortions of their views and even of their physical appearance; (5) the press does a poor job of covering suburban-rural races and independent fact checking is virtually nonexistent; and (6) since 9/11, terrorism has become a major issue and women are apt to be portrayed as too inexperienced to be trusted with protecting the national defense.     

Positive Social Support,Negative Social Exchanges,and Suicidal Behavior in College Students

Abstract

Objective: Risk for suicide is often higher among college students, compared to same-age noncollegiate peers, and may be exacerbated by quality of social support and interactions. The authors examined the independent contributions of positive social support and negative social exchanges to suicide ideation and attempts in college students. Participants: Participants were 439 volunteer undergraduate students, who were primarily female (71%). Methods: Cross-sectional, survey design. Participants completed measures assessing positive social support, including emotional, informational, and tangible support; negative social exchanges; and suicidal behavior, including ideation and attempts. Results: Positive social support, particularly tangible support, and negative social exchanges were significantly predictive of greater suicidal behavior. Conclusions: Practical manifestations of support may buffer against suicide risk for college students, whereas conflict-based interactions may contribute to increased risk. At the institutional, parental, and peer levels, promotion of supportive relationships may be an important suicide prevention strategy.