Feature LDA: a supervised topic model for automatic detection of Web API documentations from the Web

Web APIs have gained increasing popularity in recent Web service technology development owing to its simplicity of technology stack and the proliferation of mashups. However, efficiently discovering Web APIs and the relevant documentations on the Web is still a challenging task even with the best resources available on the Web. In this paper we cast the problem of detecting the Web API documentations as a text classification problem of classifying a given Web page as Web API associated or not. We propose a supervised generative topic model called feature latent Dirichlet allocation (feaLDA) which offers a generic probabilistic framework for automatic detection of Web APIs. feaLDA not only captures the correspondence between data and the associated class labels, but also provides a mechanism for incorporating side information such as labelled features automatically learned from data that can effectively help improving classification performance. Extensive experiments on our Web APIs documentation dataset shows that the feaLDA model outperforms three strong supervised baselines including naive Bayes, support vector machines, and the maximum entropy model, by over 3% in classification accuracy. In addition, feaLDA also gives superior performance when compared against other existing supervised topic models

The State of Theory in LGBTQ Aging: Implications for Gerontological Scholarship

Social research in lesbian, gay, bisexual, transgender, and queer (LGBTQ) aging is a rapidly growing field, but an examination of the use of theory has not yet been conducted for its impact on the field’s direction. We conducted a systematic review of empirical articles published in LGBTQ aging in the years 2009–2017 (N = 102). Using a typology of theory use in scholarly articles, we analyzed these articles for the types of theories being used, the degree to which theories were used in each article, and the analytical function they served. We found that 52% of articles consistently applied theory, 23% implied or partially applied theory, and 25% presented as atheoretical. A wide range of theories were used and served multiple analytical functions such as concept development and explanation of findings. We discuss the strengths and weaknesses of theory use in this body of literature, especially with respect to implications for future knowledge development in the field

A hierarchical latent response model for inferences about examinee engagement in terms of guessing and item‐level non‐response

In low‐stakes assessments, test performance has few or no consequences for examinees themselves, so that examinees may not be fully engaged when answering the items. Instead of engaging in solution behaviour, disengaged examinees might randomly guess or generate no response at all. When ignored, examinee disengagement poses a severe threat to the validity of results obtained from low‐stakes assessments. Statistical modelling approaches in educational measurement have been proposed that account for non‐response or for guessing, but do not consider both types of disengaged behaviour simultaneously. We bring together research on modelling examinee engagement and research on missing values and present a hierarchical latent response model for identifying and modelling the processes associated with examinee disengagement jointly with the processes associated with engaged responses. To that end, we employ a mixture model that identifies disengagement at the item‐by‐examinee level by assuming different data‐generating processes underlying item responses and omissions, respectively, as well as response times associated with engaged and disengaged behaviour. By modelling examinee engagement with a latent response framework, the model allows assessing how examinee engagement relates to ability and speed as well as to identify items that are likely to evoke disengaged test‐taking behaviour. An illustration of the model by means of an application to real data is presented

Interview Language: A Proxy Measure for Acculturation Among Asian Americans in a Population-Based Survey

We examined health status and access to care among Asian Americans by the following acculturation indicators: nativity, percent lifetime in the US, self-rated English proficiency, and interview language, to assess whether any measure better distinguishes acculturation. Data from the 2003 California Health Interview Survey were used to study the sample of 4,170 US-born and foreign-born Asians by acculturation indicators. We performed t-tests to compare differences in demographics, health status and behaviors, and access to care between the foreign-born and US-born Asians, and between various classifications within foreign-born and the US-born Asian group. Our results showed that foreign-born Asians who interviewed in English more closely resembled US-born Asians than foreign-born Asians who interviewed in languages other than English. Compared to interview language, dichotomizing the sample by other acculturation indicators showed smaller differences between the divided groups. Interview language may serve as a better measure for acculturation especially among foreign-born populations with a high proportion of limited English proficiency. In immigrant public health research studies, interview language may be used as an important covariate for health disparities

A simple measure with complex determinants: investigation of the correlates of self-rated health in older men and women from three continents

Self-rated health is commonly employed in research studies that seek to assess the health status of older individuals. Perceptions of health are, however, influenced by individual and societal level factors that may differ within and between countries. This study investigates levels of self-rated health (SRH) and correlates of SRH among older adults in Australia, United States of America (USA), Japan and South Korea. We conclude that when examining correlates of SRH, the similarities are greater than the differences between countries. There are however differences in levels of SRH which are not fully accounted for by the health correlates. Broad generalizations about styles of responding are not helpful for understanding these differences, which appear to be country- and possibly cohort-specific. When using SRH to characterize the health status of older people, it is important to consider earlier life experiences of cohorts as well as national and individual factors in later life. Further research is required to understand the complex societal influences on perceptions of health.The Australian data on which this research is based were drawn from several Australian longitudinal studies including: the Australian Longitudinal Study of Ageing (ALSA), the Australian Longitudinal Study of Women’s Health (ALSWH) and the Personality And Total Health Through Life Study (PATH). These studies were pooled and harmonized for the Dynamic Analyses to Optimize Ageing (DYNOPTA) project. DYNOPTA was funded by a National Health and Medical Research Council (NHMRC) grant (# 410215)

Physiotherapeutic interventions in multiple sclerosis across Europe: Regions and other factors that matter.

BACKGROUND: A wide variety of interventions exists in physical therapy (PT), but knowledge about their use across different geographical regions is limited. This study investigated the use of PT interventions in people with multiple sclerosis (MS) across Europe. It aimed to determine whether regions differ in applying interventions, and explore whether factors other than regions play a role in their use. METHODS: In an online cross-sectional survey, 212 respondents from 115 European workplaces providing PT services to people with MS representing 26 countries (four European regions) participated. Cluster analysis, Pearson Chi-squared test and a Poisson regression model were used to analyze the data. RESULTS: Thirteen of 45 listed PT interventions were used by more than 75% of centers, while nine interventions were used by less than 25%. For 12 interventions, regions differed markedly in their use. Cluster analysis of centers identified four clusters similar in their intervention use. Cluster assignment did not fully align with regions. While center region was important, center size, number and gender of physical therapists working in the center, and time since qualification also played a role. Cluster analysis exploring the use of the interventions provided the basis for a categorization of PT interventions in line with their primary focus: 1. Physical activity (fitness/endurance/resistance) training; 2. Neuroproprioceptive "facilitation/inhibition"; 3. Motor/skill acquisition (individualized therapy led); 4. Technology based interventions. CONCLUSIONS: To our knowledge this is the first study that has explored this topic in MS. The results broaden our understanding of the different PT interventions used in MS, as well as the context of their use

Bayesian Analysis of Curves Shape Variation Through Registration and Regression

This manuscript reviews the use of Bayesian hierarchical curve registration in Biostatistics and Bioinformatics.Several models allowing for unit-specific random time scales are discussed and applied to longitudinal dataarising in biomedicine, pharmacokinetics and time-course genomics. We consider representations of random functionals based on P-spline priors. Under this framework, straightforward posterior simulation strategies are outlined for inference.Beyond curve registration, we discuss jointregression modeling of both random effects and population level functional quantities. Finally, the use of mixture priors is discussed in the setting of differential expression analysis