A new model of foreign media sense-making

This paper introduces a new model to represent how individuals can develop a deepened understanding of both a foreign culture and of their own culture as a result of viewing and engaging with foreign media, and in particular foreign films and television series. The model emerged from data collected in a study of how Chinese university students based in China make sense of films and television series produced in the USA and the UK. The study involved a series of semi-structured interviews during which the students were shown clips from a number of films and television series. Five categories of sense-making activities emerged from the data, together with a number of variables, which influenced the activities, and a number of levels on which the activities could be performed. The proposed model captures all of these aspects.     

A class of linear transformation models for interval censored data with a cured proportion

Interval-censored data arise due to a sequence random examination such that the failure time of interest occurs in an interval. In some medical studies, there exist long-term survivors who can be considered as permanently cured. We consider a mixed model for the uncured group coming from linear transformation models and cured group coming from a logistic regression model. For the inference of parameters, an EM algorithm is developed for a full likelihood approach. To investigate finite sample properties of the proposed method, simulation studies are conducted. The approach is applied to the National Aeronautics and Space Administration’s hypobaric decompression sickness data.     

Estimation of association parameters in copula models for bivariate left-truncated and right-censored data

We investigate the problem of estimating the association between two related survival variables when they follow a copula model and bivariate left-truncated and right-censored data are available. By expressing truncation probability as the functional of marginal survival functions, we propose a two-stage estimation procedure for estimating the parameters of Archimedean copulas. The asymptotic properties of the proposed estimators are established. Simulation studies are conducted to investigate the finite sample properties of the proposed estimators. The proposed method is applied to a bivariate RNA data.     

Robust variable selection in modal varying-coefficient models with longitudinal

In this article we present a robust and efficient variable selection procedure by using modal regression for varying-coefficient models with longitudinal data. The new method is proposed based on basis function approximations and a group version of the adaptive LASSO penalty, which can select significant variables and estimate the non-zero smooth coefficient functions simultaneously. Under suitable conditions, we establish the consistency in variable selection and the oracle property in estimation. A simulation study and two real data examples are undertaken to assess the finite sample performance of the proposed variable selection procedure.     

Estimation of factor-augmented panel regressions with weakly influential factors

The use of factor-augmented panel regressions has become very popular in recent years. Existing methods for such regressions require that the common factors are strong, an assumption that is likely to be mistaken in practice. Motivated by this, the current article offers an analysis of the effect of weak, semi-weak, and semi-strong factors on two of the most popular estimators for factor-augmented regressions, namely, principal components (PC) and common correlated effects (CCE).     

Global kernel estimator and test of varying‐coefficient autoregressive model

We propose a varying‐coefficient autoregressive model that contains additive models, varying‐ coefficient models, partially linear models and low‐dimensional interaction models as special cases. A global kernel backfitting method is proposed for the estimation and inference of parameters and unknown functions in this model. Key large‐sample results are established, including estimation consistency, asymptotic normality and the generalized likelihood ratio test for parameters and non‐parametric functions. The proposed methodology is examined by simulation studies and applied to examine the relationship between suicide news reports in the three leading newspapers and the daily number of suicides in Taiwan. The relationship between the media reporting and suicide incidence has been established and explored. The Canadian Journal of Statistics 47: 487–519; 2019 © 2019 Statistical Society of Canada     

珠江三角洲观光农业发展模式与生态经济分析

２０世纪９０年代，珠江三角洲各地观光成为全国旅游开发的新亮点。本文在学术界理论研究基础上，结合实际调查，对珠江三角洲观光农业的发展模式与经营进行探讨。同时从生态学和经济学方面对珠江三角洲观光农业的可持续发展进行了分析，并提出一些可操作的对策。     

Paternity Leave and the Motherhood Penalty: New Causal Evidence

Objective: The objective of this study was to test how a father's paternity leave affects the within‐household gender wage gap among heterosexual couples. Background: Previous studies focus on the actual number of days of leave the father takes, but if an important driver of the gender wage gap is the effect of parental leave on gender‐specific household specialization, absolute variations in the father's leave should not be the key interest. Instead, this article tests the effect of the extent of the father's leave relative to that of the mother's leave because it is this variation that plausibly affects the division of household labor and through this the within‐household gender wage gap. Method: Full sample, administrative data are from Statistics Denmark. Causal inference was facilitated by exploiting 5 Danish parental leave reforms on 5 separate samples of all households who become first‐time parents within the year before and after each reform (N₁ = 2,304; N₂ = 45,683; N₃ = 16,668; N₄ = 42,328; N₅ = 38,978). Results: Father's leave reduces the within‐household gender wage gap through increasing mother's wages. Father's leave furthermore causes an increase in total household wage incomes. Conclusion: Father's stronger involvement in the household may be one route to more gender equality, but more so to increased financial well‐being among families.     

Profile likelihood approaches for semiparametric copula and frailty models for clustered survival data

ABSTRACT

In clustered survival data, the dependence among individual survival times within a cluster has usually been described using copula models and frailty models. In this paper we propose a profile likelihood approach for semiparametric copula models with different cluster sizes. We also propose a likelihood ratio method based on profile likelihood for testing the absence of association parameter (i.e. test of independence) under the copula models, leading to the boundary problem of the parameter space. For this purpose, we show via simulation study that the proposed likelihood ratio method using an asymptotic chi-square mixture distribution performs well as sample size increases. We compare the behaviors of the two models using the profile likelihood approach under a semiparametric setting. The proposed method is demonstrated using two well-known data sets.     

Statistical considerations for crowdsourced perceptual ratings of human speech productions

Crowdsourcing has become a major tool for scholarly research since its introduction to the academic sphere in 2008. However, unlike in traditional laboratory settings, it is nearly impossible to control the conditions under which workers on crowdsourcing platforms complete tasks. In the study of communication disorders, crowdsourcing has provided a novel solution to the collection of perceptual ratings of human speech production. Such ratings allow researchers to gauge whether a treatment yields meaningful change in how human listeners' perceive disordered speech. This paper will explore some statistical considerations of crowdsourced data with specific focus on collecting perceptual ratings of human speech productions. Random effects models are applied to crowdsourced perceptual ratings collected in both a continuous and binary fashion. A simulation study is conducted to test the reliability of the proposed models under differing numbers of workers and tasks. Finally, this methodology is applied to a data set from the study of communication disorders.