A graph model for probabilities of nested conditionals

We define a model for computing probabilities of right-nested conditionals in terms of graphs representing Markov chains. This is an extension of the model for simple conditionals from Wójtowicz and Wójtowicz (Erkenntnis, 1–35. 10.1007/s10670-019-00144-z, 2019). The model makes it possible to give a formal yet simple description of different interpretations of right-nested conditionals and to compute their probabilities in a mathematically rigorous way. In this study we focus on the problem of the probabilities of conditionals; we do not discuss questions concerning logical and metalogical issues such as setting up an axiomatic framework, inference rules, defining semantics, proving completeness, soundness etc. Our theory is motivated by the possible-worlds approach (the direct formal inspiration is the Stalnaker Bernoulli models); however, our model is generally more flexible. In the paper we focus on right-nested conditionals, discussing them in detail. The graph model makes it possible to account in a unified way for both shallow and deep interpretations of right-nested conditionals (the former being typical of Stalnaker Bernoulli spaces, the latter of McGee’s and Kaufmann’s causal Stalnaker Bernoulli models). In particular, we discuss the status of the Import-Export Principle and PCCP. We briefly discuss some methodological constraints on admissible models and analyze our model with respect to them. The study also illustrates the general problem of finding formal explications of philosophically important notions and applying mathematical methods in analyzing philosophical issues.

Neonatal mortality clustering in the central districts of Ghana

Introduction Identifying high risk geographical clusters for neonatal mortality is important for guiding policy and targeted interventions. However, limited studies have been conducted in Ghana to identify such clusters. Objective This study aimed to identify high-risk clusters for all-cause and cause-specific neonatal mortality in the Kintampo Districts. Materials and methods Secondary data, comprising of 30,132 singleton neonates between January 2005 and December 2014, from the Kintampo Health and Demographic Surveillance System (KHDSS) database were used. Verbal autopsies were used to determine probable causes of neonatal deaths. Purely spatial analysis was ran to scan for high-risk clusters using Poisson and Bernoulli models for all-cause and cause-specific neonatal mortality in the Kintampo Districts respectively with village as the unit of analysis. Results The study revealed significantly high risk of village-clusters for neonatal deaths due to asphyxia (RR = 1.98, p = 0.012) and prematurity (RR = 5.47, p = 0.025) in the southern part of Kintampo Districts. Clusters (emerging clusters) which have the potential to be significant in future, for all-cause neonatal mortality was also identified in the south-western part of the Kintampo Districts. Conclusions Study findings showed cause-specific neonatal mortality clustering in the southern part of the Kintampo Districts. Emerging cluster was also identified for all-cause neonatal mortality. More attention is needed on prematurity and asphyxia in the identified cause-specific neonatal mortality clusters. The emerging cluster for all-cause neonatal mortality also needs more attention to forestall any formation of significant mortality cluster in the future. Further research is also required to understand the high concentration of prematurity and asphyxiated deaths in the identified clusters.

A zero-inflated gamma model for post-deconvolved calcium imaging traces

Calcium imaging is a critical tool for measuring the activity of large neural populations. Much effort has been devoted to developing “pre-processing” tools applied to calcium video data, addressing the important issues of e.g., motion correction, denoising, compression, demixing, and deconvolution. However, computational modeling of deconvolved calcium signals (i.e., the estimated activity extracted by a pre-processing pipeline) is just as critical for interpreting calcium measurements. Surprisingly, these issues have to date received significantly less attention. To fill this gap, we examine the statistical properties of the deconvolved activity estimates, and propose several density models for these random signals. These models include a zero-inflated gamma (ZIG) model, which characterizes the calcium responses as a mixture of a gamma distribution and a point mass which serves to model zero responses. We apply the resulting models to neural encoding and decoding problems. We find that the ZIG model out-performs simpler models (e.g., Poisson or Bernoulli models) in the context of both simulated and real neural data, and can therefore play a useful role in bridging calcium imaging analysis methods with tools for analyzing activity in large neural populations.

Neighborhoods and Intimate Partner Violence Against Women: The Direct and Interactive Effects of Social Ties and Collective Efficacy

This study examines the impact of several indicators of neighborhood social ties (e.g., residents’ interactions with each other; residents’ ability to recognize outsiders) on intimate partner violence (IPV) against women as well as whether neighborhood collective efficacy’s impact on IPV is contingent upon such ties. This study used data from 4,151 women (46% Latina, 33% African American, 17% Caucasian, on average 32 years old) in 80 neighborhoods from the Project on Human Development in Chicago Neighborhoods. We estimated a series of random effects hierarchical Bernoulli models to assess the main and interactive effects of neighborhood social ties and collective efficacy on minor and severe forms of IPV against women. Results indicate that certain neighborhood social ties are associated with higher rates of minor forms of IPV against women (but not severe forms of IPV), and collective efficacy does not appear to influence IPV against women, regardless of the level of individual or neighborhood social ties. Unlike street crime, collective efficacy does not significantly reduce IPV against women, even in neighborhoods with strong social ties that may facilitate awareness of the violence. In fact, perpetrators of minor IPV may enjoy some protective benefit in communities with social ties that make neighbors hesitant to intervene in what some might perceive as “private matters.”