Empirical evaluation of the implementation of the EMA guideline on missing data in confirmatory clinical trials: Specification of mixed models for longitudinal data in study protocols

In confirmatory clinical trials, the prespecification of the primary analysis model is a universally accepted scientific principle to allow strict control of the type I error. Consequently, both the ICH E9 guideline and the European Medicines Agency (EMA) guideline on missing data in confirmatory clinical trials require that the primary analysis model is defined unambiguously. This requirement applies to mixed models for longitudinal data handling missing data implicitly. To evaluate the compliance with the EMA guideline, we evaluated the model specifications in those clinical study protocols from development phases II and III submitted between 2015 and 2018 to the Ethics Committee at Hannover Medical School under the German Medicinal Products Act, which planned to use a mixed model for longitudinal data in the confirmatory testing strategy. Overall, 39 trials from different types of sponsors and a wide range of therapeutic areas were evaluated. While nearly all protocols specify the fixed and random effects of the analysis model (95%), only 77% give the structure of the covariance matrix used for modeling the repeated measurements. Moreover, the testing method (36%), the estimation method (28%), the computation method (3%), and the fallback strategy (18%) are given by less than half the study protocols. Subgroup analyses indicate that these findings are universal and not specific to clinical trial phases or size of company. Altogether, our results show that guideline compliance is to various degrees poor and consequently, strict type I error rate control at the intended level is not guaranteed.     

Robust inference for estimating equations with nonignorably missing data based on SIR algorithm

Nonresponse is a very common phenomenon in survey sampling. Nonignorable nonresponse – that is, a response mechanism that depends on the values of the variable having nonresponse – is the most difficult type of nonresponse to handle. This article develops a robust estimation approach to estimating equations (EEs) by incorporating the modelling of nonignorably missing data, the generalized method of moments (GMM) method and the imputation of EEs via the observed data rather than the imputed missing values when some responses are subject to nonignorably missingness. Based on a particular semiparametric logistic model for nonignorable missing response, this paper proposes the modified EEs to calculate the conditional expectation under nonignorably missing data. We can apply the GMM to infer the parameters. The advantage of our method is that it replaces the non-parametric kernel-smoothing with a parametric sampling importance resampling (SIR) procedure to avoid nonparametric kernel-smoothing problems with high dimensional covariates. The proposed method is shown to be more robust than some current approaches by the simulations.     

Testing the dilation order by using cumulative residual Tsallis entropy

In this paper, we introduce a new test for the dilation order based on cumulative residual Tsallis entropy of order α. The effect of the values of parameter α on the power of the test statistics is numerically investigated. The asymptotic distribution of the test statistic is given. The performance of the test statistic is evaluated using a simulation study. Finally, some numerical examples illustrating the theory are also given.     

Noninformative priors for the between-group variance in the unbalanced one-way random effects model with heterogeneous error variances

For the unbalanced one-way random effects model with heterogeneous error variances, we propose the non-informative priors for the between-group variance and develop the first- and second-order matching priors. It turns out that the second-order matching priors do not exist and the reference prior and Jeffreys prior do not satisfy a first-order matching criterion. We also show that the first-order matching prior meets the frequentist target coverage probabilities much better than the Jeffreys prior and reference prior through simulation study, and the Bayesian credible intervals based on the matching prior and reference prior give shorter intervals than the existing confidence intervals by examples.     

How publics’ active and passive communicative behaviors affect their tornado responses: An integration of STOPS and SMCC

During imminent threat crises, such as natural disasters, publics have minutes to decide how to respond after receiving a warning. This study advances understanding of publics’ crisis communicative and noncommunicative behaviors in the context of tornadoes through combining and extending two theories: the social-mediated crisis communication (SMCC) model and the situational theory of problem solving (STOPS). Findings from a survey of Southeast U.S. residents (n = 1,585) indicate that STOPS is internally consistent and accurate at measuring its intended outcomes of communicative action in problem solving. However, the STOPS measures do not have a significant relationship with the desirable outcome for imminent threat crisis communication: individuals following government’s protective action guidance about tornadoes. In comparison, the expanded SMCC model predicts individuals’ self-reported compliance. Finally, variables from the SMCC model and tornado-specific variables were integrated into the STOPS model to explain individuals’ communicative engagement. Implications for theory and public relations practice are discussed.     

Linear scalar-on-surface random effects regression models

Many research fields increasingly involve analyzing data of a complex structure. Models investigating the dependence of a response on a predictor have moved beyond the ordinary scalar-on-vector regression. We propose a regression model for a scalar response and a surface (or a bivariate function) predictor. The predictor has a random component and the regression model falls in the framework of linear random effects models. We estimate the model parameters via maximizing the log-likelihood with the ECME (Expectation/Conditional Maximization Either) algorithm. We use the approach to analyze a data set where the response is the neuroticism score and the predictor is the resting-state brain function image. In the simulations we tried, the approach has better performance than two other approaches, a functional principal component regression approach and a smooth scalar-on-image regression approach.     

Not a lonely crowd? Social connectedness,religious service attendance,and the spiritual but not religious

Using the 2006–2014 General Social Survey and 2006–2012 Portraits of American Life Study, I find that on three dimensions of social connectedness: social interaction frequency, core discussion network size, and number of close ties, that religious service attenders are more connected than religious non-attenders and then either spiritual nor religious, but there are few differences between attenders and the spiritual but not religious. Difference-in-differences and fixed-effects models show little evidence that switches between categories are associated with changes in connectedness, and additional models show that prior social connectedness explains only a small amount of future switches. This paper challenges assumptions that the non-religious are a homogenous group lacking the benefits provided though the social networks of religious congregations and has implications for research on what it means to be spiritual, measuring religion and spirituality, and understanding the role of formal organizations in social life.     

Monstrosities and moral publics

Interdisciplinary scholarship on neoliberal urban governmentality has been attentive to the knowledges and techniques of government currently emerging at the interface of local state politics and invested claims of voluntary private actors such as corporate partners and philanthropic agencies. This article draws attention to the workings of the aesthetic as an epistemological grounding for the rationalization of urban rule. Specifically, I explore a Toronto, Canada-based philanthropic agency’s reliance on a mise-en-scene of urban terror to animate its own self-validated knowledges about targeted inner-suburban subjects and spaces. In their circulation and demand for public address, the agency’s graphic public service announcements, launched in 2007, herald what I argue is a moralized set of knowledges about municipal renewal that has its own normative orientations grounded in a neoliberal political rationality, and tangentially, in racialized security imperatives. I detail various dimensions of the social life of a video associated with this public service campaign targeting ‘youth at risk’, considering the ethical, political and economic valences it was expected to convey; its semiotic exchange with other images and representations of disenfranchised spaces, subjects and communities; and the publics it attempted to interpellate. Importantly, given the agency’s current standing as a prominent player in Canadian urban policy arenas, I pay analytical attention to the visual campaign as a site for the production of knowledges about proper urban citizenship and social governance, and as such, a strategic-orienting device for urban policy interventions and directives.     

Social Skills in Children Adopted From Socially-Emotionally Depriving Institutions

This study assessed social skills in post-institutionalized (PI) children with respect to age at adoption, age at assessment, and gender. Parent ratings of social skills (Social Skills Rating System) and behavior problems (Child Behavior Checklist) were obtained for 214 children and 127 adolescents who were adopted from socially-emotionally depriving Russian institutions. Results showed that children adopted before 18 months of age have better social skills than those adopted after this age; those assessed in childhood demonstrate better social skills than those assessed in adolescence. PI females, especially later-adopted adolescents, have particularly poor social skills. Children with poor social skills tend to have higher rates of behavior problems.     

Is the web a promising tool for data collection in developing countries? An analysis of the sample bias of 10 web and face-to-face surveys from Africa,Asia, and South America

Whereas the sample composition biases of web surveys have been discussed extensively for developed countries, studies for developing countries are scarce. This article helps to fill that gap by comparing similar non-probability-based web surveys (WEB) and probability-based face-to-face (F2F) surveys both to each other and to the labor force. An analysis of WageIndicator data on work and wages derived from surveys held in 2009–2013 in 10 developing countries (WEB-sample N = 9135; F2F-sample N = 14,659), shows that F2F samples resemble the labor force to a larger extent than web samples do. In both cases, individuals in their 20s and early 30s are overrepresented, and younger and older respondents are underrepresented. This trend is more pronounced in WEB than in F2F samples. However, the differences converge in countries with higher Internet usage. A comparison of the WEB and F2F samples shows that compositions differ greatly, with web respondents being younger, more often male, more often living alone, and higher educated, although these differences are smaller in countries with higher Internet usage. Given the cost differences between the two survey modes, one should nevertheless consider the potential of web surveys as an instrument to gain explorative insights, specifically when searching for individuals with particular characteristics.