A statistical method to convert published response rates into marginal distributions with an example application in psoriasis

Assessment of severity is essential for the management of chronic diseases. Continuous variables like scores obtained from the Hamilton Rating Scale for Depression or the Psoriasis Area and Severity Index (PASI) are standard measures used in clinical trials of depression and psoriasis. In clinical trials of psoriasis, for example, the reduction of PASI from baseline in response to therapy, in particular the proportion of patients achieving at least 75%, 90%, or 100% improvement of disease (PASI 75, PASI 90, or PASI 100), is typically used to evaluate treatment efficacy. However, evaluation of the proportions of patients reaching absolute PASI values (eg, ≤1, ≤2, ≤3, or ≤5) has recently gained greater clinical interest and is increasingly being reported. When relative versus absolute scores are standard, as is the case with the PASI in psoriasis, it is difficult to compare absolute changes using existing published data. Thus, we developed a method to estimate absolute PASI levels from aggregated relative levels. This conversion method is based on a latent 2‐dimensional normal distribution for the absolute score at baseline and at a specific endpoint with a truncation to allow for baseline inclusion criterion. The model was fitted to aggregated results from simulations and from 3 phase III studies that had known absolute PASI proportions. The predictions represented the actual results quite precisely. This model might be applied to other conditions, such as depression, to estimate proportions of patients achieving an absolute low level of disease activity, given absolute values at baseline and proportions of patients achieving relative improvements at a subsequent time point.     

Anticipating acceptance of emerging technologies using twitter: the case of self-driving cars

In an early stage of developing emerging technologies, there is often great uncertainty regarding their future success. Companies can reduce this uncertainty by listening to the voice of customers as the customer eventually decides to accept an emerging technology or not. We show that risk and benefit perceptions are central determinants of acceptance of emerging technologies. We present an analysis of risk and benefit perception of self-driving cars from March 2015 until October 2016. In this period, we analyzed 1,963,905 tweets using supervised machine learning for text classification. Furthermore, we developed two new metrics, risk rate (RR) and benefit rate (BR), which allow analyzing risk and benefit perceptions on social media quantitatively. With our results, we provide impetus for further research on acceptance of self-driving cars and a methodological contribution to acceptance of emerging technologies research. Furthermore, we identify crucial issues in the public perception of self-driving cars and provide guidance for the management of emerging technologies to increase the likelihood of their acceptance.     

Parameter Estimation Algorithms for the Hyper-Gamma Distribution Class

Microcomputer-based algorithms for the estimation of the parameters shift, scale, initial and terminal shape of the hyper–Gamma distribution class are presented. They are based on the moment equations and on the logarithmic likelihood function (LLF) associated with the hyper-Gamma density. The maximum–likelihood approach is implemented by means of the derivative equations resulting from the LLF and, independently, by means of direct optimization of the LLF. Program options include estimation of (i) four parameters, (ii) three parameters (shift known), and (iii) two parameters (shift known, initial shape zero). A program diskette with user's guide will be made available upon request.     

Forecasting Contemporaneously Aggregated Vector ARMA Processes

Given a multiple time series that is generated by a multivariate ARMA process and assuming the objective is to forecast a weighted sum of the individual variables, then under a mean squared error measure of forecasting precision, it is preferable to forecast the disaggregated multiple time series and aggregate the forecasts, rather than forecast the aggregated series directly, if the involved processes are known. This result fails to hold if the processes used for forecasting are estimated from a given set of time series data. The implications of these results for empirical research are investigated using different sets of economic data.     

Testing for the Cointegrating Rank of a VAR Process With Structural Shifts

Tests for the cointegrating rank of a vector autoregressive process are considered that allow for possible exogenous shifts in the mean of the data-generation process. The break points are assumed to be known a priori. It is proposed to estimate and remove the deterministic terms such as mean, linear-trend term, and a shift in a first step. Then systems cointegration tests are applied to the adjusted series. The resulting tests are shown to have known limiting null distributions that are free of nuisance parameters and do not depend on the break point. The tests are applied for analyzing the number of cointegrating relations in two German money-demand systems.     

Family Location and Caregiving Patterns from an International Perspective

We conduct a cross‐national econometric analysis of intra‐family location and caregiving patterns. Using European data, we first assess, from an international perspective, the relationship between family structure and the geographic proximity between adult children and their parents. We then examine whether differences in family structure are related to the amount of informal care adult children provide to their elderly parents. Lastly, we look for cross‐country differences in family location and caregiving patterns, and interpret observed differences in terms of heterogeneous institutional solutions to elderly care. Our results not only provide a new empirical perspective on the geography of the family, but also provide insights into how family‐related and institutional factors shape patterns of time transfers from adult children to elderly parents.     

Estimation of structural impulse responses: short-run versus long-run identifying restrictions

There is evidence that estimates of long-run impulse responses of structural vector autoregressive (VAR) models based on long-run identifying restrictions may not be very accurate. This finding suggests that using short-run identifying restrictions may be preferable. We compare structural VAR impulse response estimates based on long-run and short-run identifying restrictions and find that long-run identifying restrictions can result in much more precise estimates for the structural impulse responses than restrictions on the impact effects of the shocks.     

Ergebnisse der Mediengewaltforschung: Überblick und Probleme

Results of media violence research: Overview and problemsOn the basis of massive acts of violence of children and young people the question arises to what extent the media make a contribution to these incidents. The results of empirical media research about the effects of the consumption of violence representations in the media are collected. As the basis for the argumentation predominantly the existing metaanalysis in the international research literature were used; with these can be convincingly argued against those theses, put again and again into the public in order to weaken the importance of medium influence. The theses set up in the public discourse are arranged thereby in the sense of an ?encyclopaedia of popular mistakes“, which are analyzed critically and disproved.On the basis of a multifactor model about the emergence of acts of violence the ways of how medium representations can affect behaviour are delineated. The view presented actually in the empirical media research corresponds neither to the frequently postulated and roughly simplifying imitation thesis, still to the simple stimulus-reaction hypothesis. However, in the public discussion these and other simplifying assumptions are reiterated again and again in order to diminish the responsibility of the media. It is also to be considered that subjective evidences, after which such effects are denied, are even explanation-needy facts, which since a long time are well documented in the social-psychological research as ?Third person effect“. Additionally suggestions are made, which measures within the diverse social fields against the media flood and its effects are to be taken.     

Assisted reproductive technologies (ART) in a model of fertility choice

We examine the relationship between assisted reproductive technologies (ART) and the microeconomics of fertility choice. Along the way, we develop a model consistent with between-country differences in overall fertility and fertility timing. Our analysis of ART centers around the distinction between biomedical and behavioral effects. While improvements in ART have the biomedical effect of raising fertility, they may cause some women who would otherwise have tried to have children earlier on in life to postpone childbirth to later in life when the conception success probability is lower. This behavioral effect of postponement may reduce the fertility rate.     

Testing for the Cointegrating Rank of a VAR Process with Level Shift at Unknown Time

A systems cointegration rank test is proposed that is applicable for vector autoregressive (VAR) processes with a structural shift at unknown time. The structural shift is modeled as a simple shift in the level of the process. It is proposed to estimate the break date first on the basis of a full unrestricted VAR model. Two alternative estimators are considered and their asymptotic properties are derived. In the next step the deterministic part of the process including the shift size is estimated and the series are adjusted by subtracting the estimated deterministic part. A Johansen type test for the cointegrating rank is applied to the adjusted series. The test statistic is shown to have a well‐known asymptotic null distribution that does not depend on the break date. The performance of the procedure in small samples is investigated by simulations.