Uncovering the root cause of ethnic difference in ability testing:differential test functioning, test familiarity and trait optimism as explanations of ethnic group differences

The present research represents a coherent approach to understanding the root causes of ethnic group differences in ability test performance. Two studies were conducted, each of which was designed to address a key knowledge gap in the ethnic bias literature. In Study 1, both the LR Method of Differential Item Functioning (DIF) detection and Mixture Latent Variable Modelling were used to investigate the degree to which Differential Test Functioning (DTF) could explain ethnic group test performance differences in a large, previously unpublished dataset. Though mean test score differences were observed between a number of ethnic groups, neither technique was able to identify ethnic DTF. This calls into question the practical application of DTF to understanding these group differences. Study 2 investigated whether a number of non-cognitive factors might explain ethnic group test performance differences on a variety of ability tests. Two factors – test familiarity and trait optimism – were able to explain a large proportion of ethnic group test score differences. Furthermore, test familiarity was found to mediate the relationship between socio-economic factors – particularly participant educational level and familial social status – and test performance, suggesting that test familiarity develops over time through the mechanism of exposure to ability testing in other contexts. These findings represent a substantial contribution to the field’s understanding of two key issues surrounding ethnic test performance differences. The author calls for a new line of research into these performance facilitating and debilitating factors, before recommendations are offered for practitioners to ensure fairer deployment of ability testing in high-stakes selection processes.

Nasal Potential Difference In Cystic Fibrosis Considering Severe Cftr Mutations.

The gold standard for diagnosing cystic fibrosis (CF) is a sweat chloride value above 60 mEq/L. However, this historical and important tool has limitations; other techniques should be studied, including the nasal potential difference (NPD) test. CFTR gene sequencing can identify CFTR mutations, but this method is time-consuming and too expensive to be used in all CF centers. The present study compared CF patients with two classes I-III CFTR mutations (10 patients) (G1), CF patients with classes IV-VI CFTR mutations (five patients) (G2), and 21 healthy subjects (G3). The CF patients and healthy subjects also underwent the NPD test. A statistical analysis was performed using the Mann-Whitney, Kruskal-Wallis, χ(2), and Fisher's exact tests, α = 0.05. No differences were observed between the CF patients and healthy controls for the PDMax, Δamiloride, and Δchloride + free + amiloride markers from the NPD test. For the finger value, a difference between G2 and G3 was described. The Wilschanski index values were different between G1 and G3. In conclusion, our data showed that NPD is useful for CF diagnosis when classes I-III CFTR mutations are screened. However, if classes IV-VI are considered, the NPD test showed an overlap in values with healthy subjects.

Towards a definition of "difference" in osteoarthritis

To assess existing information regarding detectable differences in osteoarthritis (OA), a systematic literature search was conducted up to December 1999. Thirty-three articles were considered methodologically relevant to the definition and categorization of detectable differences in OA. It was determined that the musculoskeletal literature contains a wealth of information that relates to observed changes, much of which is derived from the clinical trials literature, but there have been relatively few methodological studies that have systematically evaluated the nature, categorization, and relevance of the change. Furthermore, most of those that have been published take the perspective of an individual or groups of experts other than that of the patient. This summary of the current literature reveals that the diverse sources of information go part way towards developing an understanding of detectable differences and their importance in the area of OA research and clinical practice. Stakeholders' interests as well as factors that modulate perceptions of importance need to be taken under consideration. In particular, the patient's perspective of the importance of change at an individual level requires further evaluation. This area of clinical research is relatively underdeveloped, but there is considerable opportunity for progress.

Difference in the in-hospital mortality of unstable angina pectoris between men and women

PURPOSE: To assess differences in the in-hospital mortality (HM) rate between men and women with unstable angina pectoris (UA) according to age, depression of the ST segment, history of previous acute myocardial infarction (AMI), and risk factors for coronary heart disease. METHODS: From October 96 to March 98, 261 patients with UA were selected. Logistic regression models were developed to adjust the association between sex and HM for possible influence of covariables, such as hypertension, diabetes mellitus, dyslipidemia, sedentary lifestyle, smoking, and familial history of early coronary heart disease. RESULTS: HM due to UA was approximately three times higher in women (9.3%; 12/129) than in men (3.0%; 4/132) accounting for a relative risk of 3.07; 95% confidence interval (CI) =1.02-9.27. In logistic regression models, the association between sex and death was not significantly altered when the following parameters were considered: age, depression of the ST segment, history of previous AMI and risk factors for coronary heart disease. The nonadjusted and adjusted odds ratio (OR) for the distinct covariables were 3.28 (CI 95%=1.03-10.45) and 3.14 (CI = 95% = 0.88-11.20), respectively. CONCLUSION: Similarly to AMI, HM in UA is higher in women than in men. Age, risk factors for coronary heart disease, and depression of the ST segment in the electrocardiogram on patients' admission to the hospital did not significantly influence the association between sex and death.

Is there a difference in artistic ability between learning -disabled students and "regular-class" students?

Research and practice regarding LO students usually has focussed upon defining and supplementing deficiencies rather than seeking unique talents and capability patterns for learning and expression. This study examined nine dimensions that may constitute artistic or creative talent and compared LDs with "regular-class" students, pair-wise and as groups, for levels and distributions of the dimensions. For 14 LO and 9 "regular-class" elementary-school subjects, both genders, data were taken by direct observation, from a standardized test and assessments by two practicing artists. Assessments by artists were in concord. LOs improved more in "Composition". No other significant class, age or gender-related differences were found.

Diversity and difference in the everyday lives of Ugandan street children: The significance of age and gender for understanding the use of space

Childhood is characterised by diversity and difference across and within societies. Street children have a unique relationship to the urban environment evident through their use of the city. The everyday geographies that street children produce are diversified through the spaces they frequent and the activities they engage in. Drawing on a range of children-centred qualitative methods, this article focuses on street children's use of urban space in Kampala, Uganda. The article demonstrates the importance of considering variables such as gender and age in the analysis of street children's socio-spatial experiences, which, to date, have rarely been considered in other accounts of street children's lives. In addition the article highlights the need for also including street children's individuality and agency into understanding their use of space. The article concludes by arguing for policies to be sensitive to the diversity that characterises street children's lives and calls for a more nuanced approach where policies are designed to accommodate street children's age and gender differences, and their individual needs, interests and abilities.

Diversity and difference in the everyday lives of Ugandan street children: The significance of age and gender for understanding the use of space

Childhood is characterised by diversity and difference across and within societies. Street children have a unique relationship to the urban environment evident through their use of the city. The everyday geographies that street children produce are diversified through the spaces they frequent and the activities they engage in. Drawing on a range of children-centred qualitative methods, this article focuses on street children's use of urban space in Kampala, Uganda. The article demonstrates the importance of considering variables such as gender and age in the analysis of street children's socio-spatial experiences, which, to date, have rarely been considered in other accounts of street children's lives. In addition the article highlights the need for also including street children's individuality and agency into understanding their use of space. The article concludes by arguing for policies to be sensitive to the diversity that characterises street children's lives and calls for a more nuanced approach where policies are designed to accommodate street children's age and gender differences, and their individual needs, interests and abilities.

Inference in differences-in-differences with few treated groups and heteroskedasticity

Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we can model the heteroskedasticity of a linear combination of the errors. We show that this assumption can be satisfied without imposing strong assumptions on the errors in common DID applications. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative inference method that relies on strict stationarity and ergodicity of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment periods. We extend our inference methods to linear factor models when there are few treated groups. We also derive conditions under which a permutation test for the synthetic control estimator proposed by Abadie et al. (2010) is robust to heteroskedasticity and propose a modification on the test statistic that provided a better heteroskedasticity correction in our simulations.

Inference in differences-in-differences with few treated groups and heteroskedasticity

Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we know how the heteroskedasticity is generated, which is the case when it is generated by variation in the number of observations per group. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative application of our method that relies on assumptions about stationarity and convergence of the moments of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment groups. We extend our inference method to linear factor models when there are few treated groups. We also propose a permutation test for the synthetic control estimator that provided a better heteroskedasticity correction in our simulations than the test suggested by Abadie et al. (2010).

There is no difference in nitric oxide metabolites and neonatal outcome between premature infants born to pre-eclamptic and those born to normotensive women

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A sex difference in seasonal timing of birth in a livebearing fish

Sex differences in seasonal timing include differences in hatch- or birth-date distribution and differences in the timing of migration or maturation such as protandrous arrival timing (PAT), which is early male arrival at breeding sites. I describe a novel form of protandrous arrival timing, as a sex difference in birth-date distribution in a live-bearing fish (Dwarf Perch, Micrometrus minimus). In this species, birth coincides with arrival at breeding sites because newborn males are sexually active. A series of samples of pregnant females and young of year was collected in Tomales Bay, CA. I analyzed the daily age record in otoliths to estimate the conception date of broods and the age that young-of-year individuals were born. Males were born at a younger age than females, as indicated by the daily age record and also by the predominance of females in broods from which some young had already been born, which was a common occurrence in pregnant females with older embryos. Sex ratio of broods varied with conception date such that early-season broods were predominantly male, possibly as a result of temperature-dependent sex determination. The combined effects of the sex difference in age at birth and seasonal shift in sex ratio were to shift the mean birth date of males relative to females by five days. The most likely ultimate explanation for PAT in the Dwarf Perch is that it arises from exploitation (scramble) competition for mating opportunities among recently-born young-of-year males.

Gender Difference in Emotional and Behavioral Responses of Being Rendered Invisible

This study examined gender differences in emotional and behavioral responses to an experience of being invisible to others. Invisibility was defined as being ignored, slighted and overlooked by others. Participants recalled their own experience and answered questions about it and their responses on an anonymous web-based survey. Although such experiences could be very unpleasant, people may respond to such negative experiences very differently. It was hypothesized that in a patriarchal society like the United States in which men hold more power than women, that men would show emotion that was more aggressive such as anger, and respond more violently to incidents they were not respected. Women, on the other hand, were expected to be more subservient in their behavior and responses, show submissive emotions such as sadness, and respond less violently when they were not respected.

Cooperative or collaborative learning: Is there a difference in university students’ perceptions?

The hypothesis that the same educational objective, raised as cooperative or collaborative learning in university teaching does not affect students’ perceptions of the learning model, leads this study. It analyses the reflections of two students groups of engineering that shared the same educational goals implemented through two different methodological active learning strategies: Simulation as cooperative learning strategy and Problem-based Learning as a collaborative one. The different number of participants per group (eighty-five and sixty-five, respectively) as well as the use of two active learning strategies, either collaborative or cooperative, did not show differences in the results from a qualitative perspective.