Random effect exponentiated-exponential geometric model for clustered/longitudinal zero-inflated count data

For count responses, there are situations in biomedical and sociological applications in which extra zeroes occur. Modeling correlated (e.g. repeated measures and clustered) zero-inflated count data includes special challenges because the correlation between measurements for a subject or a cluster needs to be taken into account. Moreover, zero-inflated count data are often faced with over/under dispersion problem. In this paper, we propose a random effect model for repeated measurements or clustered data with over/under dispersed response called random effect zero-inflated exponentiated-exponential geometric regression model. The proposed method was illustrated through real examples. The performance of the model and asymptotical properties of the estimations were investigated using simulation studies.KEYWORDS: Count model, under- and over-dispersion, zero-inflation, mixture model, zero-inflated poisson model     

The analysis of incontinence episodes and other count data in patients with overactive bladder by Poisson and negative binomial regression

Clinical studies in overactive bladder have traditionally used analysis of covariance or nonparametric methods to analyse the number of incontinence episodes and other count data. It is known that if the underlying distributional assumptions of a particular parametric method do not hold, an alternative parametric method may be more efficient than a nonparametric one, which makes no assumptions regarding the underlying distribution of the data. Therefore, there are advantages in using methods based on the Poisson distribution or extensions of that method, which incorporate specific features that provide a modelling framework for count data. One challenge with count data is overdispersion, but methods are available that can account for this through the introduction of random effect terms in the modelling, and it is this modelling framework that leads to the negative binomial distribution. These models can also provide clinicians with a clearer and more appropriate interpretation of treatment effects in terms of rate ratios. In this paper, the previously used parametric and non‐parametric approaches are contrasted with those based on Poisson regression and various extensions in trials evaluating solifenacin and mirabegron in patients with overactive bladder. In these applications, negative binomial models are seen to fit the data well. Copyright © 2014 John Wiley & Sons, Ltd.     

The discursive construction of gay teenagers in times of mediatization: youth's reflections on intimate storytelling,queer shame and realness in popular social media places

New media applications such as social networking sites are understood as important evolutions for queer youth. These media and communication technologies allow teenagers to transgress their everyday life places and connect with other queer teens. Moreover, social media websites could also be used for real political activism such as publicly sharing coming out videos on YouTube. Despite these increased opportunities for self-reflexive storytelling on digital media platforms, their everyday use and popularity also bring particular complexities in the everyday lives of young people. Talking to 51 youngsters between 13 and 19 years old in focus groups, this paper inquires how young audiences discursively constructed meanings on intimate storytelling practices such as interpreting intimate stories, reflecting on their own and other peers' intimate storytelling practices. Specifically focusing on how they relate to intimate storytelling practices of gay peers, this paper identified particular challenges for queer youth who transgress the heteronormative when being active on popular social media. The increasing mediatization of intimate youth cultures brings challenges for queer teenagers, which relate to authenticity, (self-) surveillance and fear of imagined audiences.     

Pseudo-likelihood inference for clustered binary data

The maximum likelihood procedure to estimate paraneters of a model has scveral attractive properties including the existence of the covariance matrix which yield asymptotic covariances: for a sample size N the asymptotics are in general of order 1/N. Here we give an asymptotic for the skewness of the distribution of the maximum likelihood estimator of a parameter; this is of order 1/ n2 and this expression is new. Applications relate to the parameters of (i) the Poisson, binomial, and normal density. (ii) the gamna density and (iii) the Beta debsity. Other application are being considered. The expression for the asymptotic skowness at one phase of the study tured out to be unusually complicated involving the asymptotic expressions for variance and bias. When these were identified a much simpler compact expression appeared which we now describe. The work is a much improved treatment of the subject described in Shenton and Bowman (Mariunm likelihood estimation in small samples, Griffin. 1977).     

MEASURING LABOR MARKET FRICTIONS: A CROSS‐COUNTRY COMPARISON

In this paper we define and estimate measures of labor market frictions using data on job durations. We compare different estimation methods and different types of data. We propose and apply an unconditional inference method that can be applied to aggregate duration data. It does not require wage data, it is invariant to the way in which wages are determined, and it allows workers to care about other job characteristics. The empirical analysis focuses on France, but we perform separate analyses for the United States of America, the United Kingdom, Germany, and the Netherlands. We quantify the monopsony power due to search frictions and we examine the policy effects of the minimum wage, unemployment benefits, and search frictions. (JEL: J63, J64)