Challenges in Survey Research

While being an important and often used research method, survey research has been less often discussed on a methodological level in empirical software engineering than other types of research. This chapter compiles a set of important and challenging issues in survey research based on experiences with several large-scale international surveys. The chapter covers theory building, sampling, invitation and follow-up, statistical as well as qualitative analysis of survey data and the usage of psychometrics in software engineering surveys.Comment: Accepted version of chapter in the upcoming book on Contemporary Empirical Methods in Software Engineering. Update includes revision of typos and additional figures. Last update includes fixing two small issues and typo

Transparent Meta-Analysis of Prospective Memory and Aging

Prospective memory (ProM) refers to our ability to become aware of a previously formed plan at the right time and place. After two decades of research on prospective memory and aging, narrative reviews and summaries have arrived at widely different conclusions. One view is that prospective memory shows large age declines, larger than age declines on retrospective memory (RetM). Another view is that prospective memory is an exception to age declines and remains invariant across the adult lifespan. The present meta-analysis of over twenty years of research settles this controversy. It shows that prospective memory declines with aging and that the magnitude of age decline varies by prospective memory subdomain (vigilance, prospective memory proper, habitual prospective memory) as well as test setting (laboratory, natural). Moreover, this meta-analysis demonstrates that previous claims of no age declines in prospective memory are artifacts of methodological and conceptual issues afflicting prior research including widespread ceiling effects, low statistical power, age confounds, and failure to distinguish between various subdomains of prospective memory (e.g., vigilance and prospective memory proper)

Sex-Specific Genetic Structure and Social Organization in Central Asia: Insights from a Multi-Locus Study

In the last two decades, mitochondrial DNA (mtDNA) and the non-recombining portion of the Y chromosome (NRY) have been extensively used in order to measure the maternally and paternally inherited genetic structure of human populations, and to infer sex-specific demography and history. Most studies converge towards the notion that among populations, women are genetically less structured than men. This has been mainly explained by a higher migration rate of women, due to patrilocality, a tendency for men to stay in their birthplace while women move to their husband's house. Yet, since population differentiation depends upon the product of the effective number of individuals within each deme and the migration rate among demes, differences in male and female effective numbers and sex-biased dispersal have confounding effects on the comparison of genetic structure as measured by uniparentally inherited markers. In this study, we develop a new multi-locus approach to analyze jointly autosomal and X-linked markers in order to aid the understanding of sex-specific contributions to population differentiation. We show that in patrilineal herder groups of Central Asia, in contrast to bilineal agriculturalists, the effective number of women is higher than that of men. We interpret this result, which could not be obtained by the analysis of mtDNA and NRY alone, as the consequence of the social organization of patrilineal populations, in which genetically related men (but not women) tend to cluster together. This study suggests that differences in sex-specific migration rates may not be the only cause of contrasting male and female differentiation in humans, and that differences in effective numbers do matter

The Brain Matures with Stronger Functional Connectivity and Decreased Randomness of Its Network

We investigated the development of the brain's functional connectivity throughout the life span (ages 5 through 71 years) by measuring EEG activity in a large population-based sample. Connectivity was established with Synchronization Likelihood. Relative randomness of the connectivity patterns was established with Watts and Strogatz' (1998) graph parameters C (local clustering) and L (global path length) for alpha (∼10 Hz), beta (∼20 Hz), and theta (∼4 Hz) oscillation networks. From childhood to adolescence large increases in connectivity in alpha, theta and beta frequency bands were found that continued at a slower pace into adulthood (peaking at ∼50 yrs). Connectivity changes were accompanied by increases in L and C reflecting decreases in network randomness or increased order (peak levels reached at ∼18 yrs). Older age (55+) was associated with weakened connectivity. Semi-automatically segmented T1 weighted MRI images of 104 young adults revealed that connectivity was significantly correlated to cerebral white matter volume (alpha oscillations: r = 33, p<01; theta: r = 22, p<05), while path length was related to both white matter (alpha: max. r = 38, p<001) and gray matter (alpha: max. r = 36, p<001; theta: max. r = 36, p<001) volumes. In conclusion, EEG connectivity and graph theoretical network analysis may be used to trace structural and functional development of the brain

Determination of the pK(a) of the N-terminal amino group of ubiquitin by NMR

This work was supported by the Medical Research Council (grants U117533887 and grant U117565398 until March 2015) and by the Francis Crick Institute which receives its core funding from Cancer Research UK (FC001142, FC10029), the UK Medical Research Council (FC001142, FC10029), and the Wellcome Trust (FC001142, FC10029)

A synthetic ion transporter that disrupts autophagy and induces apoptosis by perturbing cellular chloride concentrations

Perturbations in cellular chloride concentrations can affect cellular pH, autophagy and lead to the onset of apoptosis. With this in mind synthetic ion transporters have been used to disturb cellular ion homeostasis and thereby induce cell death; however, it is not clear whether synthetic ion transporters can also be used to disrupt autophagy. Here we show that squaramide-based ion transporters enhance the transport of chloride anions in liposomal models and promote sodium chloride influx into the cytosol. Liposomal and cellular transport activity of the squaramides is shown to correlate with cell death activity, which is attributed to caspase-dependent apoptosis. One ion transporter was also shown to cause additional changes in the lysosomal pH which leads to impairment of lysosomal enzyme activity and disruption of autophagic processes. This disruption is independent of the initiation of apoptosis by the ion transporter. This study provides the first experimental evidence that synthetic ion transporters can disrupt both autophagy and induce apoptosis

The role of intracellular trafficking of CdSe/ZnS QDs on their consequent toxicity profile

Nanoparticle interactions with cellular membranes and the kinetics of their transport and localization are important determinants of their functionality and their biological consequences. Understanding these phenomena is fundamental for the translation of such NPs from in vitro to in vivo systems for bioimaging and medical applications. Two CdSe/ZnS quantum dots (QD) with differing surface functionality (NH2 or COOH moieties) were used here for investigating the intracellular uptake and transport kinetics of these QDs.status: publishe

Lag length selection and p-hacking in Granger causality testing: prevalence and performance of meta-regression models

The academic system incentivizes p-hacking, where researchers select estimates and statistics with statistically significant p-values for publication. We analyze the complete process of Granger causality testing including p-hacking using Monte Carlo simulations. If the degrees of freedom of the underlying vector autoregressive model are small to moderate, information criteria tend to overfit the lag length and overfitted vector autoregressive models tend to result in false-positive findings of Granger causality. Researchers may p-hack Granger causality tests by estimating multiple vector autoregressive models with different lag lengths and then selecting only those models that reject the null of Granger non-causality for presentation in the final publication. We show that overfitted lag lengths and the corresponding false-positive findings of Granger causality can frequently occur in research designs that are prevalent in empirical macroeconomics. We demonstrate that meta-regression models can control for spuriously significant Granger causality tests due to overfitted lag lengths. Finally, we find evidence that false-positive findings of Granger causality may be prevalent in the large literature that tests for Granger causality between energy use and economic output, while we do not find evidence for a genuine relation between these variables as tested in the literature