Multiple imputation of missing categorical data using latent class models:State of art

This paper provides an overview of recent proposals for using latent class models for the multiple imputation of missing categorical data in large-scale studies. While latent class (or finite mixture) modeling is mainly known as a clustering tool, it can also be used for density estimation, i.e., to get a good description of the lower- and higher-order associations among the variables in a dataset. For multiple imputation, the latter aspect is essential in order to be able to draw meaningful imputing values from the conditional distribution of the missing data given the observed data. We explain the general logic underlying the use of latent class analysis for multiple imputation. Moreover, we present several variants developed within either a frequentist or a Bayesian framework, each of which overcomes certain limitations of the standard implementation. The different approaches are illustrated and compared using a real-data psychological assessment application

Prevalence, Treatment, and Prognosis of Tumor Thrombi in Renal Cell Carcinoma

BACKGROUND Renal cell carcinoma (RCC) can be complicated by a venous tumor thrombus (TT), of which the optimal management is unknown.OBJECTIVES This study sought to assess the prevalence of TT in RCC, its current management, and its association with venous thromboembolism (VTE), arterial thromboembolism (ATE), major bleeding (MB), and mortality.METHODS Patients diagnosed with RCC between 2010 and 2019 in our hospital were included and followed from RCC diagnosis until 2 years after, or until an outcome of interest (VTE, ATE, and MB) or death occurred, depending on the analysis. Cumulative incidences were estimated with death as a competing risk. Cause-specific hazard models were used to identify predictors and the prognostic impact.RESULTS Of the 647 patients, 86 had a TT (prevalence 13.3%) at RCC diagnosis, of which 34 were limited to the renal vein, 37 were limited to the inferior vena cava below the diaphragm, and 15 extended above the diaphragm; 20 patients started therapeutic anticoagulation and 45 underwent thrombectomy with/without anticoagulation. During follow-up (median 24.0 [IQR: 7.0-24.0] months), 17 TT patients developed a VTE, 0 developed an ATE, and 11 developed MB. TT patients were more often diagnosed with VTE (adjusted HR: 6.61; 95% CI: 3.18-13.73) than non-TT patients, with increasing VTE risks in more proximal TT levels. TT patients receiving anticoagulation still developed VTE (HR: 0.56; 95% CI: 0.13-2.48), at the cost of more MB events (HR: 3.44; 95% CI: 0.95-12.42) compared with those without anticoagulation.CONCLUSIONS Patients with RCC-associated TT were at high risk of developing VTE. Future studies should establish which of these patients benefit from anticoagulation therapy. (c) 2022 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Tissue-specific suppression of thyroid hormone signaling in various mouse models of aging

DNA damage contributes to the process of aging, as underscored by premature aging syndromes caused by defective DNA repair. Thyroid state changes during aging, but underlying mechanisms remain elusive. Since thyroid hormone (TH) is a key regulator of metabolism, changes in TH signaling have widespread effects. Here, we reveal a significant common transcriptomic signature in livers from hypothyroid mice, DNA repair-deficient mice with severe (Csbm/m/Xpa-/-) or intermediate (Ercc1-/Δ-7) progeria and naturally aged mice. A strong induction of TH-inactivating deiodinase D3 and decrease of TH-activating D1 activities are observed in Csbm/m/Xpa-/- livers. Similar findings are noticed in Ercc1-/Δ-7, in naturally aged animals and in wild-type mice exposed to a chronic subtoxic dose of DNAdamaging agents. In contrast, TH signaling in muscle, heart and brain appears unaltered. These data show a strong suppression of TH signaling in specific peripheral organs in premature and normal aging, probably lowering metabolism, while other tissues appear to preserve metabolism. D3-mediated TH inactivation is unexpected, given its expression mainly in fetal tissues. Our studies highlight the importance of DNA damage as the underlying mechanism of changes in thyroid state. Tissue-specific regulation of deiodinase activities, ensuring diminished TH signaling, may contribute importantly to the protective metabolic response in aging

RStorm: Developing and testing streaming algorithms in R

Contains fulltext : 133517.pdf (publisher's version ) (Open Access)Streaming data, consisting of indefinitely evolving sequences, are becoming ubiquitous in many branches of science and in various applications. Computer scientists have developed streaming applications such as Storm and the S4 distributed stream computing platform1 to deal with data streams. However, in current production packages testing and evaluating streaming algorithms is cumbersome. This paper presents RStorm for the development and evaluation of streaming algorithms analogous to these production packages, but implemented fully in R. RStorm allows developers of streaming algorithms to quickly test, iterate, and evaluate various implementations of streaming algorithms. The paper provides both a canonical computer science example, the streaming word count, and examples of several statistical applications of RStorm.10 p

Combining multiple influence strategies to increase consumer compliance

Contains fulltext : 143337.pdf (publisher's version ) (Open Access)In this paper, we investigate the effects and implications of utilising multiple social influence strategies simultaneously to endorse a single product or call to action. In three, studies we show that combinations of social influence strategies do not increase compliance - this is contrary to commonly held beliefs and practice. Studies 1 and 2 show that combining implementations of both the consensus and authority strategies to promote a single behaviour does not lead to an increase in the effectiveness of a persuasive attempt. In Study 3, we test these findings in an online advertising campaign and again show that a single influence strategy is more effective than the combined usage of multiple influence strategies. The paper outlines the importance of appropriately choosing and implementing social influence strategies to prevent unintended interactions between the strategies that lead to a suboptimal performance

Using generalized linear (mixed) models in HCI

In HCI we often encounter dependent variables which are not (conditionally) normally distributed: we measure response-times, mouse-clicks, or the number of dialog steps it took a user to complete a task. Furthermore, we often encounter nested or grouped data; users are grouped within companies or institutes, or we obtain multiple observations within users. The standard linear regression models and ANOVAs used to analyze our experimental data are not always feasible in such cases since their assumptions are violated, or the predictions from the fitted models are outside the range of the observed data. In this chapter we introduce extensions to the standard linear model (LM) to enable the analysis of these data. The use of [R] to fit both Generalized Linear Models (GLMs) as well as Generalized Linear Mixed Models (GLMMs, also known as random effects models or hierarchical models) is explained. The chapter also briefly covers regularized regression models which are hardly used in the social sciences despite the fact that these models are extremely popular in Machine Learning, often for good reasons. We end with a number of recommendations for further reading on the topics that are introduced: the current text serves as a basic introduction

Adaptive persuasive messaging to increase service retention: using persuasion profiles to increase the effectiveness of email reminders

Contains fulltext : 129956.pdf (publisher's version ) (Open Access)In this article, we describe the usage of persuasion profiles in a large scale, N = 1,129, field trial. Persuasive technologies-technologies intentionally designed to influence user behavior-are emergent and becoming more and more individualized and ubiquitous. Individual differences in people's responses to often used persuasion principles-different psychological means by which to influence users-motivate personalization. We describe how, through identification, representation, and measurement, persuasive technologies can personalize their persuasive attempts. Next, we show that dynamically adapting a persuasive technology to the responses of its users increases the effectiveness of the system. Ubiquitous computing systems are, because of their ability to unobtrusively measure user behavior, very well suited for these types of applications

Improving statistical practice in HCI

So you have come to the end. You have, if all is according to plan, learned novel methods and have started to think fairly critically about the methods that are of common use in HCI. Perhaps you are convinced that we could, and should, improve our reporting practice. The previous chapter has highlighted, practically without reference to specific methods or choosing a "camp" (Bayesian or Frequentist), a large number of possible directions for improvements

Customizing persuasive messages:The value of operative measures

Purpose This paper aims to examine whether estimates of psychological traits obtained using meta-judgmental measures (as commonly present in customer relationship management database systems) or operative measures are most useful in predicting customer behavior. Design/methodology/approach Using an online experiment (N = 283), the study collects meta-judgmental and operative measures of customers. Subsequently, it compares the out-of-sample prediction error of responses to persuasive messages. Findings The study shows that operative measures – derived directly from measures of customer behavior – are more informative than meta-judgmental measures. Practical implications Using interactive media, it is possible to actively elicit operative measures. This study shows that practitioners seeking to customize their marketing communication should focus on obtaining such psychographic observations. Originality/value While currently both meta-judgmental measures and operative measures are used for customization in interactive marketing, this study directly compares their utility for the prediction of future responses to persuasive messages