Identification, Inference and Sensitivity Analysis for Causal Mediation Effects

Causal mediation analysis is routinely conducted by applied researchers in a variety of disciplines. The goal of such an analysis is to investigate alternative causal mechanisms by examining the roles of intermediate variables that lie in the causal paths between the treatment and outcome variables. In this paper we first prove that under a particular version of sequential ignorability assumption, the average causal mediation effect (ACME) is nonparametrically identified. We compare our identification assumption with those proposed in the literature. Some practical implications of our identification result are also discussed. In particular, the popular estimator based on the linear structural equation model (LSEM) can be interpreted as an ACME estimator once additional parametric assumptions are made. We show that these assumptions can easily be relaxed within and outside of the LSEM framework and propose simple nonparametric estimation strategies. Second, and perhaps most importantly, we propose a new sensitivity analysis that can be easily implemented by applied researchers within the LSEM framework. Like the existing identifying assumptions, the proposed sequential ignorability assumption may be too strong in many applied settings. Thus, sensitivity analysis is essential in order to examine the robustness of empirical findings to the possible existence of an unmeasured confounder. Finally, we apply the proposed methods to a randomized experiment from political psychology. We also make easy-to-use software available to implement the proposed methods.Comment: Published in at http://dx.doi.org/10.1214/10-STS321 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Resonant Control of Interaction Between Different Electronic States

We observe a magnetic Feshbach resonance in a collision between the ground and metastable states of two-electron atoms of ytterbium (Yb). We measure the on-site interaction of doubly-occupied sites of an atomic Mott insulator state in a three-dimensional optical lattice as a collisional frequency shift in a high-resolution laser spectroscopy. The observed spectra are well fitted by a simple theoretical formula, in which two particles with an s-wave contact interaction are confined in a harmonic trap. This analysis reveals a wide variation of the interaction with a resonance behavior around a magnetic field of about 1.1 Gauss for the energetically lowest magnetic sublevel of ${}^{170}$Yb, as well as around 360 mG for the energetically highest magnetic sublevel of ${}^{174}$Yb. The observed Feshbach resonance can only be induced by an anisotropic inter-atomic interaction. This novel scheme will open the door to a variety of study using two-electron atoms with tunable interaction.Comment: 5 pages, 5 figure

Impact of Metrical Prosody on Performances

This thesis is about testing Frederick Turner and Ernst Pöppel\u27s claim that suggestmetrical poem tends to measure three seconds in terms of psychological limitwhen it is performed aloud. The objective of the study is to present metricalpoems as the new data to test their claim by using corpus analysis. Hereby, theresearcher uses publicly available 28 read-aloud poems from poetryoutloud.orgby using Praat to find the duration of each metrical line. The findings indicate thatthere are 18 English metrical poems with 314 lines in total, supported by metricaltree analysis, meanwhile there are 10 poems which are free verse and found that1) most lines have iamb feet, 2) 10 of the metrical pattern of the poems are iambicpentameter, whereas others are in diverse meter, 3) there is no psychological limiton the duration of metrical lines in performance as the researcher only founds62.73% that fit to the 3 seconds of temporal window based on the analysis in thecorpus of 314 metrical lines. This study has shown what Frederick Turner andErnst Pöppel claim is not methodologically proven

Thermodynamic and kinematic structure of tropical cyclones in the western North Pacific based on ACARS/AMDAR

Meteorological variables are often reported by commercial aircraft flying around tropical cyclones (TCs). They are archived in Aircraft Communications, Addressing, and Reporting System/Aircraft Meteorological Data Relay (ACARS/AMDAR). Therefore, they are potentially useful for constructing a composite mean structure of TCs based on in-situ measurements. The number of temperature and wind observations are 4.0 × 106 and 1.0 × 104 within the radius of 1,200 km and 100 km from the TC center during 2010–2020, respectively. The warm-core potential temperature anomaly with respect to the climatology is 6.4 K, 9.1 K, and 14.4 K maximized around 300 hPa for weak, moderate, and strong TCs, respectively. The composite of the potential temperature anomaly potentially extends more than 1,000 km from the TC center in the upper troposphere, cautioning the typical definition of the environment. The region of significant upper-level positive potential temperature anomalies extends broadly with increasing TC intensity. Moreover, large TCs tend to have a broad and deep upper-level warm core for a given intensity. In addition, we ensured that a single observation of potential temperature around 300 hPa could be used as a proxy for minimum sea level pressure. Low-level inflow and upper-level outflow were detected in the ACARS/AMDAR data

Celiac artery dissection in polycystic kidney disease

Autosomal-dominant polycystic kidney disease (ADPKD) is rarely complicated by celiac artery dissection. Dissection of the aorta and its major branches should be carefully differentiated in ADPKD patients with acute-onset abdominal pain

mediation: R package for causal mediation analysis

In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting such an analysis. The package is organized into two distinct approaches. Using the model-based approach, researchers can estimate causal mediation effects and conduct sensitivity analysis under the standard research design. Furthermore, the design-based approach provides several analysis tools that are applicable under different experimental designs. This approach requires weaker assumptions than the model-based approach. We also implement a statistical method for dealing with multiple (causally dependent) mediators, which are often encountered in practice. Finally, the package also offers a methodology for assessing causal mediation in the presence of treatment noncompliance, a common problem in randomized trials

MEASURING DYNAMIC KNEE MOTION DURING JUMP LANDING

The majority of anterior cruciate ligament (ACL) injuries in female athletes has been observed in noncontact situations such as jump landing. Theoretically, valgus and external rotation moments imposed to the knee joint will place ACL at high risk for injury (Olsen et al., 2004). Even though, it has been accepted that tibial and femoral rotation affects ACL tension, few studies have demonstrated tibial and femoral rotation angle in the relationship to neutral position. Therefore, the purpose of this study was to measure the tibial and femoral rotation angle during jump landing in female athletes

Pseudoacromegaly with acromegalic features in radiography

Pseudoacromegaly is a condition characterized by acromegalic physical features without growth hormone excess, for which radiographic observation has seldom been reported. This is a rare case of pseudoacromegaly

Priming bias versus post-treatment bias in experimental designs

Conditioning on variables affected by treatment can induce post-treatment bias when estimating causal effects. Although this suggests that researchers should measure potential moderators before administering the treatment in an experiment, doing so may also bias causal effect estimation if the covariate measurement primes respondents to react differently to the treatment. This paper formally analyzes this trade-off between post-treatment and priming biases in three experimental designs that vary when moderators are measured: pre-treatment, post-treatment, or a randomized choice between the two. We derive nonparametric bounds for interactions between the treatment and the moderator in each design and show how to use substantive assumptions to narrow these bounds. These bounds allow researchers to assess the sensitivity of their empirical findings to either source of bias. We extend the basic framework in two ways. First, we apply the framework to the case of post-treatment attention checks and bound how much inattentive respondents can attenuate estimated treatment effects. Second, we develop a parametric Bayesian approach to incorporate pre-treatment covariates in the analysis to sharpen our inferences and quantify estimation uncertainty. We apply these methods to a survey experiment on electoral messaging. We conclude with practical recommendations for scholars designing experiments.Comment: 32 pages (main text), 18 pages (supplementary materials), 4 figure