On general consistency in deconvolution mode estimation

This paper addresses the problem of estimating the mode of a density function based on contaminated data. Unlike conventional methods, which are based on localizing the maximum of a density estimator, we introduce a procedure which requires computation of the maximum among finitely many quantities only. We show that our estimator is strongly consistent under very weak conditions, where not even continuity of the density at the mode is required; moreover, we show that the estimator achieves optimal convergence rates under common smoothness and sharpness constraints. Some numerical simulations are provided.     

Mixture experiments with mixing errors

In mixture experiments the properties of mixtures are usually studied by mixing the amounts of the mixture components that are required to obtain the necessary proportions. This paper considers the impact of inaccuracies in discharging the required amounts of the mixture components on the statistical analysis of the data. It shows how the regression calibration approach can be used to minimize the resulting bias in the model and in the estimates of the model parameters, as well as to find correct estimates of the corresponding variances. Its application is made difficult by the complex structure of these errors. We also show how knowledge of the form of the model bias allows for choosing a manufacturing setting for a mixture product that is not biased and has smaller signal to noise ratio.     

Nonparametric estimation of the conditional mean residual life function with censored data

The conditional mean residual life (MRL) function is the expected remaining lifetime of a system given survival past a particular time point and the values of a set of predictor variables. This function is a valuable tool in reliability and actuarial studies when the right tail of the distribution is of interest, and can be more informative than the survivor function. In this paper, we identify theoretical limitations of some semi-parametric conditional MRL models, and propose two nonparametric methods of estimating the conditional MRL function. Asymptotic properties such as consistency and normality of our proposed estimators are established. We investigate via simulation study the empirical properties of the proposed estimators, including bootstrap pointwise confidence intervals. Using Monte Carlo simulations we compare the proposed nonparametric estimators to two popular semi-parametric methods of analysis, for varying types of data. The proposed estimators are demonstrated on the Veteran’s Administration lung cancer trial.     

Gauging the unique developmental strategies towards human resource at Saudi Aramco

Saudi Aramco’s unrivalled upstream oil operations over the years would not have been possible without an unparalleled commitment towards the development of people. The human resource department of Saudi Aramco was successful in creating a healthy and productive environment by shifting the focus from ‘administration’ to being a ‘strategic partner’. The purpose of this paper is to identify and illuminate the human resource developmental strategies that are aligned with core business practices leading to exceptional performance at Saudi Aramco. As an academician, the author believes that this paper will provide an insight into gauging human resource development strategies for any aspiring firm and can be referred for further research.     

Leading collective action to address wicked problems

The alleviation of wicked problems requires collective action because these issues are characterized by significant uncertainty and complexity. This research extends prior work by examining how conveners' use robust action to navigate wicked problems' defining characteristics in the mobilization process. It provides a longitudinal study of a health care nonprofit attempting to engage other stakeholders in addressing the high costs and inadequate quality of health care in a region of the United States. Specifically, the convener sought to address this wicked problem by developing a health information exchange. The findings relate five robust action tactics through which the convener advanced collective action.     

GPU-accelerated Gibbs sampling: a case study of the Horseshoe Probit model

Statistics and Computing - Gibbs sampling is a widely used Markov chain Monte Carlo (MCMC) method for numerically approximating integrals of interest in Bayesian statistics and other mathematical...     

The Effects of Questionnaire Translation on Demographic Data and Analysis

The collection of demographic data in developing and, increasingly, developed countries often requires the translation of a survey instrument. This article addresses the implications for data and analysis of two of the most common modes of translation. The first, the officially sanctioned—though not empirically verified—method, involves the pre-fieldwork production of a standardized translation of the template questionnaire into all or most languages in which interviews are expected to be conducted. The second, rarely acknowledged in the literature but quite common in the field, occurs where there is a mismatch between the language of the questionnaire available to the interviewer and the language in which the actual interview is conducted. In this case, it is up to the interviewer to translate from the language of the questionnaire to the language of the interview. Using the 1998 Kenya DHS, in which 23% of interviews were translated in this non-standardized manner, we explore the effects of the two translation modes on three indicators of measurement error and on estimated multivariate relations. In general we find that the effects of non-standardized translation on univariate statistics—including higher-order variance structures—are rather moderate. The effects become magnified, however, when multivariate analysis is used. This suggests that the advantages of—and also costs associated with—standardized translation depend on the ultimate purposes of data collection.

Measuring Homonegativity: Psychometric Analysis of Herek’s Attitudes Toward Lesbians and Gay Men Scale (ATLG) in Colombia,South America

The empirical study of negative attitudes toward gay and lesbian people (homonegativity) is a way to understand the reason for its prevalence. The aim of this study was to examine the psychometric properties of a Spanish version of the Attitudes Toward Lesbians and Gay Men Scale (ATLG). A total of 359 undergraduate students were recruited from two different cities in Colombia, South America. Participants’ attitudes toward gays and lesbian people were assessed using the ATLG Scale and the Homophobia Scale; anxiety was measured using a short version of the Zung Self-Rating Anxiety Scale. Internal consistency analyses have shown that the ATLG Scale is a reliable measure of homonegativity in a Colombian sample. In addition, principal components analyses, as well as convergent and divergent validity analyses have confirmed that the ATLG Scale is a valid and reliable measure of homonegativity in the Colombian context and support its use as a research instrument.     

Taxonomic,phylogenetic and functional diversity of an urban Amazonian avifauna

Amazonia is undergoing rapid urbanisation, but nothing has been published on the structure and function of urban Amazonian avifaunas. Here we present the results of a year-long survey of the avifauna of an Amazonian city, exploring temporal variation in its taxonomic, phylogenetic and functional diversity. We found urban bird communities to be taxonomically depauperate and dominated by a small subset of common species typical of second growth and river-edge habitats. Broad patterns of phylogenetic community similarity typically resembled those found in other studies on urban Neotropical bird assemblages, with insectivores the dominant guild. There was significant temporal variation in taxonomic and phylogenetic structure owing to the seasonal arrival and departure of a regionally over-represented minority of migratory species. Although the urban avian assemblage is of limited regional conservation value, it may still offer significant biodiversity services and represent one of few points of contact for local people with biodiversity.     

Taking Big Data apart: local readings of composite media collections

If we are to think critically about Big Data initiatives, we must learn to take them apart. This paper explains how to interrogate Big Data, not as large homogenous resources, but as heterogeneous collections with varied and discordant local ties. My argument focuses on the Big Data of media collections: composite digital repositories of texts, images, and video created in different contexts, but brought together online. The primary example used in this paper is the Digital Public Library of America (DPLA), a collection composed of digitized library, museum and archive records from institutions across the United States. I demonstrate how local readings of DPLA data can uncover schemata, errors, infrastructures, classifications, absences, and rituals that have important origins. Moreover, I explain how identifying these local features can support new forms of scholarship, pedagogy, and advocacy in the face of Big Data. For this last point, I use two additional cases: NewsScape, a real-time archive of broadcast news, and Zillow, a marketplace for real estate listings. The range of examples demonstrates how the stakes change from one Big Data initiative to the next. The paper concludes with a set of speculative guidelines for attending to the local conditions in Big Data: get dirty, take a comparative approach, show context, use data to connect people, and create opportunities for the collection of counter-data. When working with Big Data, I argue that thinking locally is thinking critically.