New values of time and reliability in passenger transport in The Netherlands

We have established new values of time (VOTs) and values of travel time reliability (VORs) for use in cost-benefit analysis (CBA) of transport projects in The Netherlands. This was the first national study in The Netherlands (and one of the first world-wide) to investigate these topics empirically in a joint framework. Stated preference (SP) questionnaires were designed for interviewing travellers, where the hypothetical alternatives were described in terms of travel time, travel costs and travel time reliability, the latter being presented to the respondents in the form of five possible travel times having equal probability. For passenger transport, we first collected interviews using an existing internet panel. Additional data collection recruitment was done by asking travellers at petrol stations/service areas, parking garages, stations, bus stops, airports and ports to participate in the survey. One important conclusion is that the SP survey using members of this internet panel leads to substantially lower VOTs than the SP survey with en-route recruitment, probably because of self-selection bias in the internet panel. We estimated discrete choice models in which the values of time differ between trips with different time and costs levels, different time and costs changes offered in the SP, and different observed characteristics of the respondents (e.g. education, income, age, household composition). By using a panel latent class model, we also account for unobserved differences between respondents in the value of time and for repeated measurements/panel effects. The reference values of time and the reference reliability ratios were estimated on the 2011 sample only, but the effect of time and cost level, time and cost changes offered and socio-economic attributes was estimated on both the 2009 and 2011 samples

Values of travel time in Europe: Review and meta-analysis

This paper reports the most extensive meta-analysis of values of time yet conducted, covering 3109 monetary valuations assembled from 389 European studies conducted between 1963 and 2011. It aims to explain how valuations vary across studies, including over time and between countries. In addition to the customary coverage of in-vehicle time in review studies, this paper covers valuations of walk time, wait time, service headway, parking space search time, departure time switching, time in congested traffic, schedule delay early and late, mean lateness and the standard deviation of travel time. Valuations are found to vary with type of time, GDP, distance, journey purpose, mode, the monetary numeraire and a number of factors related to estimation. Model output values of time compare favourably with earnings data, replicate well official recommended values obtained from major national studies, and are transferable across countries. These implied monetary values serve as very useful benchmarks against which new evidence can be assessed and the meta-model provides parameters and values for countries and contexts where there is no other such evidence

Editorial : Autophagy : from big data to physiological significance

Autophagy is a fundamental catabolic process where cytoplasmic components are sequestered into double-membrane vesicles called autophagosomes, which then fuse with lysosomes and their content is degraded. Our knowledge about autophagy sharply increased during the last decade. This significant progress helped us to understand better the molecular mechanisms of autophagy and to elucidate its role in health and disease. This special issue contains a collection of three original research papers and 12 review articles covering a broad range of topics highlighting how big data and screening approaches can help toward uncovering the molecular mechanisms of autophagy

Abandon Statistical Significance

We discuss problems the null hypothesis significance testing (NHST) paradigm poses for replication and more broadly in the biomedical and social sciences as well as how these problems remain unresolved by proposals involving modified p-value thresholds, confidence intervals, and Bayes factors. We then discuss our own proposal, which is to abandon statistical significance. We recommend dropping the NHST paradigm--and the p-value thresholds intrinsic to it--as the default statistical paradigm for research, publication, and discovery in the biomedical and social sciences. Specifically, we propose that the p-value be demoted from its threshold screening role and instead, treated continuously, be considered along with currently subordinate factors (e.g., related prior evidence, plausibility of mechanism, study design and data quality, real world costs and benefits, novelty of finding, and other factors that vary by research domain) as just one among many pieces of evidence. We have no desire to "ban" p-values or other purely statistical measures. Rather, we believe that such measures should not be thresholded and that, thresholded or not, they should not take priority over the currently subordinate factors. We also argue that it seldom makes sense to calibrate evidence as a function of p-values or other purely statistical measures. We offer recommendations for how our proposal can be implemented in the scientific publication process as well as in statistical decision making more broadly

Daubert\u27s Significance

The authors review and note the limited reach of Daubert v. Merrell Dow Pharmaceuticals. They also address its implications for concerned non-lawyers