From Data to Causes II: Comparing Approaches to Panel Data Analysis

This article compares a general cross-lagged model (GCLM) to other panel data methods based on their coherence with a causal logic and pragmatic concerns regarding modeled dynamics and hypothesis testing. We examine three “static” models that do not incorporate temporal dynamics: random- and fixed-effects models that estimate contemporaneous relationships; and latent curve models. We then describe “dynamic” models that incorporate temporal dynamics in the form of lagged effects: cross-lagged models estimated in a structural equation model (SEM) or multilevel model (MLM) framework; Arellano-Bond dynamic panel data methods; and autoregressive latent trajectory models. We describe the implications of overlooking temporal dynamics in static models and show how even popular cross-lagged models fail to control for stable factors over time. We also show that Arellano-Bond and autoregressive latent trajectory models have various shortcomings. By contrasting these approaches, we clarify the benefits and drawbacks of common methods for modeling panel data, including the GCLM approach we propose. We conclude with a discussion of issues regarding causal inference, including difficulties in separating different types of time-invariant and time-varying effects over time

From Data to Causes I: Building A General Cross-Lagged Panel Model (GCLM)

This is the first paper in a series of two that synthesizes, compares, and extends methods for causal inference with longitudinal panel data in a structural equation modeling (SEM) framework. Starting with a cross-lagged approach, this paper builds a general cross-lagged panel model (GCLM) with parameters to account for stable factors while increasing the range of dynamic processes that can be modeled. We illustrate the GCLM by examining the relationship between national income and subjective well-being (SWB), showing how to examine hypotheses about short-run (via Granger-Sims tests) versus long-run effects (via impulse responses). When controlling for stable factors, we find no short-run or long-run effects among these variables, showing national SWB to be relatively stable, whereas income is less so. Our second paper addresses the differences between the GCLM and other methods. Online Supplementary Materials offer an Excel file automating GCLM input for Mplus (with an example also for Lavaan in R) and analyses using additional data sets and all program input/output. We also offer an introductory GCLM presentation at https://youtu.be/tHnnaRNPbXs. We conclude with a discussion of issues surrounding causal inference

Infrastructure for Detector Research and Development towards the International Linear Collider

The EUDET-project was launched to create an infrastructure for developing and testing new and advanced detector technologies to be used at a future linear collider. The aim was to make possible experimentation and analysis of data for institutes, which otherwise could not be realized due to lack of resources. The infrastructure comprised an analysis and software network, and instrumentation infrastructures for tracking detectors as well as for calorimetry.Comment: 54 pages, 48 picture

Group identities benefit well-being by satisfying needs

Although research has highlighted the importance of differentiating between different types of social ties – group ties and individual ties – no experimental work exists that investigates the claim that group ties are more beneficial than individual ties, and little is known about how group memberships influence well-being, relative to relationships. We designed a series of experiments that: a) primed either multiple group memberships or multiple interpersonal relationships (vs. films) and observed the effects on participants’ induced negative moods (S1, N = 120); b) primed different types (S2, N = 317) and features (S3, N = 183) of groups and observed which led to the greatest increases in life satisfaction; and c) investigated whether feelings of connectedness and self-worth mediated these effects (S1-3). We found that priming relationships satisfied psychological needs and restored and enhanced well-being, but that priming group memberships did so to a greater extent, especially when participants reflected on the group’s identity rather than its members. This work contributes to our understanding of why multiple group memberships are beneficial, and highlights how important social identities associated with groups can be for well-being

First record of Rhabdoceras suessi (Ammonoidea, Late Triassic) from the Transylvanian Triassic Series of the Eastern Carpathians (Romania) and a review of its biochronology, paleobiogeography and paleoecology

Abstract The occurrence of the heteromorphic ammonoid Rhabdoceras suessi Hauer, 1860, is recorded for the first time in the Upper Triassic limestone of the Timon-Ciungi olistolith in the Rarău Syncline, Eastern Carpathians. A single specimen of Rhabdoceras suessi co-occurs with Monotis (Monotis) salinaria that constrains its occurrence here to the Upper Norian (Sevatian 1). It is the only known heteromorphic ammonoid in the Upper Triassic of the Romanian Carpathians. Rhabdoceras suessi is a cosmopolitan species widely recorded in low and mid-paleolatitude faunas. It ranges from the Late Norian to the Rhaetian and is suitable for high-resolution worldwide correlations only when it co-occurs with shorter-ranging choristoceratids, monotid bivalves, or the hydrozoan Heterastridium. Formerly considered as the index fossil for the Upper Norian (Sevatian) Suessi Zone, by the latest 1970s this species lost its key biochronologic status among Late Triassic ammonoids, and it generated a controversy in the 1980s concerning the status of the Rhaetian stage. New stratigraphic data from North America and Europe in the subsequent decades resulted in a revised ammonoid biostratigraphy for the uppermost Triassic, the Rhaetian being reinstalled as the topmost stage in the current standard timescale of the Triassic. The geographic distribution of Rhabdoceras is compiled from published worldwide records, and its paleobiogeography and paleoecology are discussed

Predictors of response to psychological treatment in somatoform disorder and somatic symptom disorder: A meta-analysis

Aims: Somatoform disorder and somatic symptom disorder are associated with substantial psychosocial and functional impairment. Meta-analysis can clarify whether this group of disorders tends to be difficult to treat and whether effects of therapy depend on specific variables. The main aim of the present meta-analysis was to examine whether type of intervention and type of outcome variable predicted response to treatment. Methods: Included were studies evaluating a psychological intervention given to patients diagnosed with somatoform disorder or somatic symptom disorder. Of 2,655 initially identified records, 22 studies were eligible for quantitative analysis, involving 3,160 patients. Outcome domains were somatic symptoms, psycho-behavioral features (e.g., psychopathology) and illness consequences (e.g., mental and physical well-being and functioning). Results: An overall medium-to-large pre-post effect size across 27 intervention conditions (d = 0.77) and a medium pre-post effect size across 10 control conditions (d = 0.49) was obtained. Psychological interventions were significantly superior to control conditions for illness consequences but not for somatic symptoms or psycho-behavioral features. Pre-post effect sizes for cognitive-behavioral therapy (CBT) did not significantly differ from those of other psychological interventions. Longer symptom duration, younger age and lower methodological quality predicted larger effect sizes. Conclusion: Overall, the present findings suggest that psychological interventions are effective in improving illness consequences but may not yield larger amounts of change when compared to control conditions in terms of symptoms or psychopathology. Effects of CBT did not prove superior to effects of other psychological interventions. Relatively modest effects of treatment and the difficulty of identifying modifiable predictors of treatment effects, such as type of treatment, provide support for previous suggestions in the literature that somatoform disorder is difficult to treat

High mobility group box protein 1 neutralization therapy in ovine bacteremia: lessons learned from an ovine septic shock model incorporating intensive care support

Sepsis is a highly complex and often fatal syndrome which varies widely in its clinical manifestations, and therapies that target the underlying uncontrolled immune status in sepsis are needed. The failure of preclinical approaches to provide significant sepsis survival benefit in the clinic is often attributed to inappropriate animal disease models. It has been demonstrated that high mobility group box protein 1 (HMGB1) blockade can reduce inflammation, mortality and morbidity in experimental sepsis without promoting immunosuppression. Within this study, we explored the use of ovine anti-HMGB1 antibodies in a model of ovine septic shock incorporating intensive care supports (OSSICS). Results: Septic sheep exhibited elevated levels of HMGB1 within 12 h after the induction of sepsis. In this study, sepsis was induced in six anaesthetized adult Border Leicester × Merino ewes via intravenous instillation of E. coli and sheep monitored according to intensive care unit standard protocols for 26 h, with the requirement for noradrenaline as the primary endpoint. Septic sheep exhibited a hyperdynamic circulation, renal dysfunction, deranged coagulation profile and severe metabolic acidosis. Sheep were assigned a severity of illness score, which increased over time. While a therapeutic effect of intravenous anti-HMGB1 antibody could not be observed in this model due to limited animal numbers, a reduced bacterial dose induced a septic syndrome of much lower severity. With modifications including a reduced bacterial dose, a longer timeframe and broad spectrum antibiotics, the OSSICS model may become a robust tool for preclinical assessment of sepsis therapeutics.Natalie E. Stevens, Coralie H. Nash, Cara K. Fraser, Tim R. Kuchel, Matthew J. Maiden, Marianne J. Chapman, Kerrilyn R. Diener, and John D. Haybal