Estimation of Sample Size and Power For Quantile Regression

Quantile regression (QR) was first introduced by Roger Koenker and Gilbert Bassett in 1978. It is robust to outliers which affect least squares estimator on a large scale in linear regression. Instead of modeling mean of the response, QR provides an alternative way to model the relationship between quantiles of the response and covariates. Therefore, QR can be widely used to solve problems in econometrics, environmental sciences and health sciences. Sample size is an important factor in the planning stage of experimental design and observational studies. In ordinary linear regression, sample size may be determined based on either precision analysis or power analysis with closed form formulas. There are also methods that calculate sample size based on precision analysis for QR like C.Jennen-Steinmetz and S.Wellek (2005). A method to estimate sample size for QR based on power analysis was proposed by Shao and Wang (2009). In this paper, a new method is proposed to calculate sample size based on power analysis under hypothesis test of covariate effects. Even though error distribution assumption is not necessary for QR analysis itself, researchers have to make assumptions of error distribution and covariate structure in the planning stage of a study to obtain a reasonable estimate of sample size. In this project, both parametric and nonparametric methods are provided to estimate error distribution. Since the method proposed can be implemented in R, user is able to choose either parametric distribution or nonparametric kernel density estimation for error distribution. User also needs to specify the covariate structure and effect size to carry out sample size and power calculation. The performance of the method proposed is further evaluated using numerical simulation. The results suggest that the sample sizes obtained from our method provide empirical powers that are closed to the nominal power level, for example, 80%.

Lost in Translation? Russian Media Portrayals and Laypersons’ Interpretations of Angelina Jolie’s Breast Cancer Discourse

In May 2013, Angelina Jolie revealed that because she had a family history of breast and ovarian cancer and carried a rare BRCA gene mutation, she had undergone a preventive double mastectomy. Media coverage has been extensive around the world, including in Russia, not an English-language country, where all global news is inevitably filtered by translation. After examining the reactions of Russian mass media and members of the public to Jolie’s disclosure, I consider what transformations have occurred with Jolie’s message in the process of cross-cultural transfer. I explore the mass media portrayal of Jolie’s announcement, laypersons’ immediate and prolonged reactions, and the reflections of patients involved directly in the field of hereditary breast cancer. To my knowledge, this multifaceted and bilingual project is the first conceptualization of Jolie’s story as it has been translated in a different sociocultural environment. I start with examination of offline and online publications that appeared in Russia within two months after Jolie’s announcement. In this part of my analysis, I conceptualize the representation of Jolie’s case in Russian mass media and grasp what sociocultural waves were generated by this case among general lay audiences. Another part of my study contains the results of qualitative in-depth interviews. Eight women with a family history of hereditary breast cancer were recruited to participate in the research. The findings represent Jolie’s case through the eyes of Russian women with the same gene mutation as Jolie. Consolidating my findings, I argue that Jolie’s announcement was misinterpreted and misrepresented by Russian mass media, as well as misunderstood by a considerable part of the media audience. Jolie’s perspective on hereditary breast cancer mostly remained unheard among members of the Russian public. I make suggestions about the reasons for such a phenomenon, and demonstrate how Jolie’s case is implicated in politics, economics, and the culture of contemporary Russia.