Hypothesis Formalization: Empirical Findings, Software Limitations, and Design Implications

Data analysis requires translating higher level questions and hypotheses into computable statistical models. We present a mixed-methods study aimed at identifying the steps, considerations, and challenges involved in operationalizing hypotheses into statistical models, a process we refer to as hypothesis formalization . In a formative content analysis of 50 research papers, we find that researchers highlight decomposing a hypothesis into sub-hypotheses, selecting proxy variables, and formulating statistical models based on data collection design as key steps. In a lab study, we find that analysts fixated on implementation and shaped their analyses to fit familiar approaches, even if sub-optimal. In an analysis of software tools, we find that tools provide inconsistent, low-level abstractions that may limit the statistical models analysts use to formalize hypotheses. Based on these observations, we characterize hypothesis formalization as a dual-search process balancing conceptual and statistical considerations constrained by data and computation and discuss implications for future tools.

Invertebrate dispersal by waterbird species in neotropical wetlands

Endozoochory by waterbirds is particularly relevant to the dispersal of non-flying aquatic invertebrates. This ecological function exercised by birds has been demonstrated in different biogeographical regions, but there are no studies for the neotropical region. In this work, we identified propagules of invertebrates in faeces of 14 syntopic South American waterbird species representing six families, and hatched additional invertebrates from cultured faeces. We tested whether propagule abundance, species richness and composition varied among bird species, and between the cold and warm seasons. We found 164 invertebrate propagules in faecal samples from seven different waterbirds species, including eggs of the Temnocephalida and Notonectidae, statoblasts of bryozoans (Plumatella sp.) and ephippia of Cladocera. Ciliates (including Paramecium sp. and Litostomatea), nematodes and rotifers (Adineta sp. and Nottomatidae) hatched from cultured samples. Potential for endozoochory was confirmed for 12 of 14 waterbird species. Our statistical models suggest that richness and abundance of propagules are associated with bird species and not affected by seasonality. Dispersal by endozoochory is potentially important to a broad variety of invertebrates, being promoted by waterbirds with different ecological and morphological traits, which are likely to drive the dispersal of invertebrates in neotropical wetlands.

Weighted Relative Group Entropies and Associated Fisher Metrics

A large family of new α-weighted group entropy functionals is defined and associated Fisher-like metrics are considered. All these notions are well-suited semi-Riemannian tools for the geometrization of entropy-related statistical models, where they may act as sensitive controlling invariants. The main result of the paper establishes a link between such a metric and a canonical one. A sufficient condition is found, in order that the two metrics be conformal (or homothetic). In particular, we recover a recent result, established for α=1 and for non-weighted relative group entropies. Our conformality condition is “universal”, in the sense that it does not depend on the group exponential.

Epistatic models predict mutable sites in SARS-CoV-2 proteins and epitopes

The emergence of new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major concern given their potential impact on the transmissibility and pathogenicity of the virus as well as the efficacy of therapeutic interventions. Here, we predict the mutability of all positions in SARS-CoV-2 protein domains to forecast the appearance of unseen variants. Using sequence data from other coronaviruses, preexisting to SARS-CoV-2, we build statistical models that not only capture amino acid conservation but also more complex patterns resulting from epistasis. We show that these models are notably superior to conservation profiles in estimating the already observable SARS-CoV-2 variability. In the receptor binding domain of the spike protein, we observe that the predicted mutability correlates well with experimental measures of protein stability and that both are reliable mutability predictors (receiver operating characteristic areas under the curve ∼0.8). Most interestingly, we observe an increasing agreement between our model and the observed variability as more data become available over time, proving the anticipatory capacity of our model. When combined with data concerning the immune response, our approach identifies positions where current variants of concern are highly overrepresented. These results could assist studies on viral evolution and future viral outbreaks and, in particular, guide the exploration and anticipation of potentially harmful future SARS-CoV-2 variants.

Models of Privacy and Disclosure on Social Networking Sites: A Systematic Literature Review

Social networking sites (SNSs) are used widely, raising new issues in terms of privacy and disclosure. Although users are often concerned about their privacy, they often publish information on social networking sites willingly. Due to the growing number of users of social networking sites, substantial research has been conducted in recent years. In this paper, we conducted a systematic review of papers that included structural equations models (SEM), or other statistical models with privacy and disclosure constructs. A total of 98 such papers were found and included in the analysis. In this paper, we evaluated the presentation of results of the models containing privacy and disclosure constructs. We carried out an analysis of which background theories are used in such studies and have also found that the studies have not been carried out worldwide. Extending the research to other countries could help with better user awareness of the privacy and self-disclosure of users on SNSs.