Covariance Terms Research Articles

Bayesian Model Averaging for Satellite Models in Bank's Credit Risk Projections

Satellite Models are usually used by banks to project the impact of a given scenario, usually expressed in terms of macroeconomic and financial covariates, of various risk parameters, such as Loss Given Default (LGD) and Probability of Default (PD). These projections are needed in various contexts (ICAAP, Stress Testing, IFRS9 Provisioning, Recovery Plan) where usually the problem at hand is often sparse: we have relatively few observations of the risk parameter compared to the number of covariates available. To overcome the criticism of cherry picking related to any specific model, i.e. subset of covariates, a Bayesian Model Average approach has been suggested, as in [Gross and Poblacion, 2004] and [Sala-i Martin et al., 2004], where one samples the model space and an average projection is taken weighting the sampled models in terms of a penalized likelihood as in the Bayesian Information Criterion (BIC). The advantage of this approach lies in its ease of implementation involving OLS estimates. Also from a theoretical standpoint the suggested approach can be considered an asymptotic proxy of any bayesian model for a wide class of prior distributions on the covariates parameters. Here we will test the approach proposed in [Gross and Poblacion, 2004] and [Sala-i Martin et al., 2004] against a hierarchical empirical bayesian model on both simulated and real credit risk datasets showing how the two approaches give similar results in terms of fit and forecast distribution. Nevertheless the weights associated to the sampled models can significantly differ making the bayesian model a safer choice.

264. Anti-platelet Therapy Significantly Reduces Inpatient Mortality in Patients with Staphylococcus aureus Bacteremia

BackgroundThere is a growing body of evidence which suggests that P2Y12 inhibitors may have antibacterial properties in vivo. To our knowledge, this has not been previously examined using real world clinical data from patients with specific infections.MethodsOur retrospective cohort study included patients admitted to Veterans Affairs hospitals between 2010–2018 with blood cultures positive for S. aureus and treated with appropriate antibiotics within 48 hours of culture collection. We included patients treated with P2Y12 inhibitors for at least the 30 days prior to admission and continued use for at least 5 days after admission. Non-users included patients without P2Y12 inhibitor use in the year prior to admission through discharge. We compared clinical outcomes during the S. aureus bacteremia admission among P2Y12 users and non-users using propensity score matched Cox proportional hazards regression models.ResultsWe identified 371 P2Y12 inhibitor users (clopidogrel, prasugrel, ticagrelor, cangrelor) and 13,298 non-users. Mean age was 70 years and 69 years, respectively. Over 98% were male in both the groups, and the overall inpatient mortality rate was 8.7%. We were able to match 199 users and non-users, which were well matched in terms of baseline covariates. Inpatient mortality was significantly lower among P2Y12 inhibitor users (hazard ratio [HR] 0.08, 95% confidence interval [CI] 0.01–0.64), and 30-day mortality was non-significantly lower (HR 0.57, 95% CI 0.31–1.03). There was no difference between the groups in readmission or re-infection within 30 days of discharge.ConclusionAmong patients with S. aureus bacteremia, those treated with P2Y12 inhibitors in the days leading up to admission and continuing through the initial period of antibiotic treatment, had a 92% lower risk of inpatient mortality. Identifying adjunctive therapies which improve clinical outcomes among patients with S. aureus bacteremia is highly important in order to improve patient outcomes and to increase the understanding of the pathophysiology of the disease. Prospective clinical studies are needed to further define the potential benefits of P2Y12 inhibitors in S. aureus bacteremia and possibly other infection types.Disclosures Aisling Caffrey, PhD, Merck (Research Grant or Support)Pfizer (Research Grant or Support)Shionogi (Research Grant or Support) Erlinda R. Ulloa, MD, MSc, Cidara Therapeutics (Consultant) Victor Nizet, MD, Centauri Therapeutics (Advisor or Review Panel member)Cidara Therapeutics (Advisor or Review Panel member)InhibRx (Advisor or Review Panel member)Roche Pharmaceutical (Advisor or Review Panel member) Kerry LaPlante, PharmD, Merck (Advisor or Review Panel member, Research Grant or Support)Ocean Spray Cranberries, Inc. (Research Grant or Support)Pfizer Pharmaceuticals (Research Grant or Support)Shionogi, Inc. (Research Grant or Support)

Sex Differences in Postoperative Complications and Functional Status After Deformity Correction Surgery: Do Men Fare Better Than Women?

We investigated whether a sex-related difference exists in the postoperative complication risk and health-related quality of life measures after surgery for adult spinal deformity. We performed a retrospective study of 156 adult patients with a diagnosis of adult spinal deformity who had undergone spinal surgery. The primary outcome variables included the postoperative complication rates and changes in the health-related quality of life measures. Adjusted odds ratios were estimated by multivariate logistic regression with the inclusion of covariate terms for sex, smoking, preoperative optimization, American Society of Anesthesiologists grade, depression, osteoporosis, invasiveness of surgery (number of vertebral levels fused), and baseline functional disability. At presentation, the women were more likely to be smokers (74 women [71.15%]; 23 men [42.31%]; P=0.01) and to have a greater prevalence of depression (36 women [34.62%]; 10 men [19.23%]; P= 0.06). The women had also presented with more severe baseline pain (visual analog scale for back pain score, 7.24 vs. 6.00 [P=0.02]; visual analog scale for leg pain score, 5.87 vs. 5.59 [P= 0.07]) and worse functional disability (patient-reported outcomes measurement information system score, 6.82 vs. 5.65 [P= 0.01]; Oswestry disability index, 45.42 vs. 37.07 [P= 0.01]). However, postoperatively, the women experienced greater improvement in pain and disability compared with the men. The unadjusted odds of a postoperative complication was greater for the women (odds ratio, 1.14; 95% confidence interval, 0.55-2.33). On multivariate logistic regression analysis, the association between sex and postoperative complications was attenuated after controlling for other baseline variables. In the present study, after adjustment for important baseline prognostic factors, no differences were found in the postoperative complication rates or extent of functional improvement when stratified by sex. Both sexes responded equally well to corrective surgery for symptomatic adult spinal deformity.

Investigation of the Validity and Reliability of a Placement Quality Survey for Measuring Rural Student Work Integrated Learning Placement Quality

This study assessed the validity and reliability of the Placement Quality Survey (PQS) for measuring rural student clinical placement quality among allied health students attending rural placements. Secondly, the association of the PQS with students’ choice of rural placements and rural self-efficacy was determined. Students attending 5–8-week placements completed a paper-based questionnaire and were also invited to complete it again later the same day for reliability testing. Reliability and validity were tested. Analysis of variance was used to investigate relationships between PQS items and composite scores with student discipline, venue of student placement, and rural self-efficacy. Occupational therapy, physiotherapy and speech pathology students (N = 163) participated. From the exploratory factor analysis a single factor was extracted which accounted for 62.1% of the variance. The standard one factor confirmatory factor analysis demonstrated reasonable fit but with the addition of a covariance term provided a good fit. Increased preference for rural placements was demonstrated for eight out of nine nine-item PQS items. Rural self-efficacy increased quality ratings, supporting construct validity. The Cronbach’s alpha indicated a high level of internal consistency. All item-to-item correlations indicated a high level of consistency. Test-retest Pearson’s correlations and intraclass correlation coefficients of repeatability indicated the reliability of the scale over time. This study validated the PQS in a sample of rural allied-health students. The results provided support for reliability. The study addresses the critical need for placement quality data to improve allied health students’ experiences and learning outcomes on placements and encourage systematic quality improvement processes.

A Comparison Study of Goodness of Fit Tests of Logistic Regression in R: Simulation and Application to Breast Cancer Data

Goodness of fit (GOF) tests of logistic regression attempt to find out the suitability of the model to the data. The null hypothesis of all GOF tests is the model fit. R as a free software package has many GOF tests in different packages. A Monte Carlo simulation has been conducted to study two situations; the first, studying the ability of each test, under its default settings, to accept the null hypothesis when the model truly fitted. The second, studying the power of these tests when assumptions of sufficient linear combination of the explanatory variables are violated (by omitting linear covariate term, quadratic term, or interaction term). Moreover, checking whether the same test in different R packages had the same results or not. As the sample size supposed to affect simulation results, so the pattern of change of GOF tests results under different sample sizes as well as different model settings was estimated. All tests accept the null hypothesis (more than 95% of simulation trials) when the model truly fitted except modified Hosmer-Lemeshow test in "LogisticDx" package under all different model settings and Osius and Rojek’s (OsRo) test when the true model had an interaction term between binary and categorical covariates. In addition, le Cessie-van Houwelingen-Copas-Hosmer unweighted sum of squares (CHCH) test gave unexpected different results under different packages. Concerning the power study, all tests had a very low power when a departure of missing covariate existed. Generally, stukel’s test (package ’LogisticDX) and CHCH test (package "RMS") reached a power in detecting a missing quadratic term greater than 80% under lower sample size while OsRo test (package ’LogisticDX’) was better in detecting missing interaction term. Beside the simulation study, we evaluated the performance of GOF tests using the breast cancer dataset.

Comparison of the performance of HYBRID ETKF-3DVAR and 3DVAR data assimilation scheme on the forecast of tropical cyclones formed over the Bay of Bengal

This study compares the performance of hybrid ensemble transform Kalman filter – three dimensional variational data assimilation (HYBRID) system and three dimensional variational (3DVAR) data assimilation system in Weather Research and Forecasting Model (WRF) in simulating tropical cyclones (TC) formed over the Bay of Bengal. An Ensemble Transform Kalman Filter (ETKF) system updates the ensemble system that provides flow-evolving background error covariance for HYBRID data assimilation system. Results indicate that use of flow-evolving ensemble error covariance in 3DVAR system has systematically reduced the TC position and intensity errors in the analysis; however, adding more weights to the ensemble error covariance term in 3DVAR cost function has not made any significant impact. The 3DVAR analysis depicts a stronger TC vortex with a well pronounced warm core structure as compared to that in HYBRID analysis. The forecasts from HYBRID analysis outperform that from 3DVAR in reducing TC track forecast error. The relative improvement in TC landfall position is 43% and 49% for variously configured HYBRID experiments. The forecasts initiated from HYBRID analysis has higher skill in quantitative precipitation forecasts during TC landfall compared to 3DVAR, which may be attributed to improved track prediction in the HYBRID experiments.

Walsh functions, scrambled [formula omitted]-nets, and negative covariance: Applying symbolic computation to quasi-Monte Carlo integration

We investigate base b Walsh functions for which the variance of the integral estimator based on a scrambled (0,m,s)-net in base b is less than or equal to that of the Monte-Carlo estimator based on the same number of points. First we compute the Walsh decomposition for the joint probability density function of two distinct points randomly chosen from a scrambled (t,m,s)-net in base b in terms of certain counting numbers and simplify it in the special case t is zero. Using this, we obtain an expression for the covariance of the integral estimator in terms of the Walsh coefficients of the function. Finally, we prove that the covariance of the integral estimator is negative when the Walsh coefficients of the function satisfy a certain decay condition. To do this, we use creative telescoping and recurrence solving algorithms from symbolic computation to find a sign equivalent closed form expression for the covariance term.

Distributed Fusion Estimation with Sensor Gain Degradation and Markovian Delays

This paper investigates the distributed fusion estimation of a signal for a class of multi-sensor systems with random uncertainties both in the sensor outputs and during the transmission connections. The measured outputs are assumed to be affected by multiplicative noises, which degrade the signal, and delays may occur during transmission. These uncertainties are commonly described by means of independent Bernoulli random variables. In the present paper, the model is generalised in two directions: (i) at each sensor, the degradation in the measurements is modelled by sequences of random variables with arbitrary distribution over the interval [0, 1]; (ii) transmission delays are described using three-state homogeneous Markov chains (Markovian delays), thus modelling dependence at different sampling times. Assuming that the measurement noises are correlated and cross-correlated at both simultaneous and consecutive sampling times, and that the evolution of the signal process is unknown, we address the problem of signal estimation in terms of covariances, using the following distributed fusion method. First, the local filtering and fixed-point smoothing algorithms are obtained by an innovation approach. Then, the corresponding distributed fusion estimators are obtained as a matrix-weighted linear combination of the local ones, using the mean squared error as the criterion of optimality. Finally, the efficiency of the algorithms obtained, measured by estimation error covariance matrices, is shown by a numerical simulation example.

Convergence to stationary non-equilibrium states for Klein–Gordon equations

We consider Klein–Gordon equations in , , with constant or variable coefficients and study the Cauchy problem with random initial data. We investigate the distribution of a random solution at moments of time . We prove the convergence of correlation functions of the measure to a limit as . The explicit formulae for the limiting correlation functions and the energy current density (in mean) are obtained in terms of the initial covariance. Furthermore, we prove the weak convergence of to a limiting measure as . We apply these results to the case when the initial random function has the Gibbs distribution with different temperatures in some infinite “parts” of the space. In this case, we find states in which the limiting energy current density does not vanish. Thus, for the model being studied, we construct a new class of stationary non-equilibrium states.

The Covert and Overt Reassurance Seeking Inventory (CORSI): Development, validation and psychometric analyses.

Reassurance seeking (RS) is motivated by perceived general and social/relational threats across disorders, yet is often under-recognized because it occurs in covert (i.e. subtle) and overt forms. Covert safety-seeking behaviour may maintain disorders by preventing corrective learning and is therefore important to identify effectively. This study presents the validation and psychometric analyses of a novel measure of covert and overt, general and social/relational threat-related interpersonal RS. An initial 30-item measure was administered to an undergraduate sample (N = 1626), as well as to samples of individuals diagnosed with obsessive compulsive disorder (OCD; n = 50), anxiety disorders (n = 60) and depression (n = 30). The data were subjected to exploratory and confirmatory factor analyses, and validation analyses. An exploratory factor analysis using principal axis factoring with oblique rotation yielded five interpretable factors, after removing four complex items. The resulting 26-item measure, the Covert and Overt Reassurance Seeking Inventory (CORSI), evidenced good convergent and divergent validity and accounted for 54.99% of the total variance after extraction. Factor correlations ranged from r = .268 to .736, suggesting that they may be tapping into unique facets of RS behaviour. In comparison with undergraduate participants, all clinical groups had significantly higher total scores [t (51.80-840) = 3.92-5.84, p < .001]. The CFA confirmed the five-factor model with good fit following the addition of four covariance terms (goodness of fit index = .897, comparative fit index = .918, Tucker-Lewis index = .907, root mean square error approximation = .061). The CORSI is a brief, yet comprehensive and psychometrically strong measure of problematic RS. With further validation, the CORSI has potential for use within clinical and research contexts.

Co-variation, style and social meaning: The implicational relationship between (h) and (ing) in Debden, Essex

AbstractThis paper demonstrates that the differing social meanings held by linguistic features can result in an implicational relationship between them. Rates of (h) and (ing) are investigated in the casual speech of sixty-three speakers from a community with Cockney heritage: Debden, Essex. The indexicalities of h-dropping in Debden (signalling Cockney) are superordinate to and incorporate the indexicalities of g-dropping (working-class, “improper”), resulting in an implicational relationship. H-dropping implies g-dropping, but g-dropping can occur independently of h-dropping. This occurs in terms of co-variation at the between-speaker level and clustering effects at the within-speaker level which is measured through a novel approach using the number of phonemes as the denomination of distance. The features’ differing social meaning are also related to rates of change. Young speakers are shifting away from linguistic features which index Cockney heritage (h-dropping; the [-Iŋk] variant of -thing words) in favor of more general, southeastern, working-class norms (g-dropping).

Assessment and comparison of five satellite precipitation products in Australia

Quality satellite-derived precipitation products (SPPs) are needed for water resources inventories and management, particularly in poorly gauged regions around the world. The latest version of five SPPs were assessed against SILO (Scientific Information for Land Owners) gauge-based gridded precipitation dataset in Australia over a 5-year period from October 2014 to September 2019. The evaluation was carried out using a 0.50° grid at daily, seasonal, and annual temporal scales. The assessed SPPs were the Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) (IMERG), TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Centre (CPC) MORPHing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and PERSIANN-CDR (Climate Data Record). PERSIANN does not include any ground-based observations for bias-correction, while the other four products are bias-corrected against gauge-based data. Bias ratio and correlation coefficient for the five SPPs showed that the overall performance of IMERG and TMPA was better than that of CMORPH, PERSIANN, and PERSIANN-CDR for Australia. Seasonal analysis showed that IMERG had the better skill in winter. Overall, IMERG appeared to be the best SPP for Australia. However, TMPA also performed reasonably well, considering the climatological calibration implemented recently in the precipitation processing algorithm. The Structural Similarity Index (SSI), a map comparison technique using a moving window-based approach, was used to compare similarities between a pair of gridded precipitation maps in terms of local mean, variance, and covariance. All the SPPs showed discrepancies in the spatial structure of the mean annual precipitation, predominantly over some high precipitation areas in Australia. These local scale differences were not detectable in conventional cell by cell comparison or simply by visual inspection. Therefore, SSI could be an effective method to evaluate satellite precipitation estimation algorithm.

Berge equilibrium in linear-quadratic mean-field-type games

In this paper, we study Berge equilibria in linear-quadratic mean-field-type game problems under a jump-diffusion-regime switching state dynamics that incorporate mean-field terms in both the states and cost functional. In the cost functional, we consider conditional variance of the states and control actions, conditional mean of states and control actions, and conditional covariance terms. The underlying Berge problem is solved in a semi-explicit way by using the direct method and an illustrative numerical example is presented.

Extending Inferences from a Cluster‐Randomized Trial to a Target Population

Research ObjectiveIn cluster‐randomized trials, participating clusters are not necessarily representative of the target population of trial‐eligible clusters where the experimental treatments might be applied. To the extent that participating and nonparticipating clusters differ in terms of covariates that are modifiers of the treatment effect, the average treatment effect in the trial may not apply to the entire target population. We describe analyses that extend (generalize or transport) causal inferences from cluster‐randomized trials to a target population of clusters, under a general nonparametric model that allows for arbitrary within‐cluster dependence.Study DesignWe consider study designs where a subset of a cohort of clusters are invited and agree to participate in a randomized trial with cluster‐level treatment assignment (ie, nested trial designs). Treatment and outcome data need only be collected from clusters participating in the trial, but data on baseline covariates must be collected from the entire cohort. We propose doubly robust estimators of potential outcome means in the target population that exploit individual‐level data on covariates and outcomes to improve efficiency and are appropriate for use with machine learning methods.Population StudiedWe illustrate the methods using a 2 × 2 factorial cluster‐randomized trial of influenza vaccination strategies conducted in 818 nursing homes nested in a cohort of 4,475 trial‐eligible Medicare‐certified nursing homes. To be eligible for the trial, nursing homes had to be free‐standing facilities (ie, not hospital based) within 50 miles of a CDC‐reporting city, have a minimum of 50 long‐stay residents, and at least 80% of residents aged 65 years or older.Principal FindingsWe applied the methods to estimate the potential outcome means for the four vaccination strategies in the target population of trial‐eligible nursing homes. We estimated the conditional probability of trial participation (nursing home level) and the conditional probability of death from any cause (individual level, separately for each treatment group) using different methods to illustrate that our approach can easily accommodate them. One set of analyses used logistic regression models estimated by maximum likelihood methods. For comparison, we also estimated probabilities using various machine learning methods. Overall, the doubly robust estimator produced similar point estimates for the potential outcome mean under each treatment across all approaches for estimating the conditional probabilities of trial participation and death. Point estimates for generalizability analyses were largely similar to those from the randomized trial, suggesting that the trial‐only estimates were applicable to the broader population of trial‐eligible nursing homes for the outcome of all‐cause death.ConclusionsRecent work on extending causal inferences from individually randomized trials to a target population can be extended to the cluster trial setting, under a general causal model that allows for arbitrary within‐cluster dependence.Implications for Policy or PracticeWhen cluster‐randomized trials are embedded in large health care systems, investigators can use the methods we describe to extend causal inferences from the trials to the broader health care system.Primary Funding SourcePatient‐Centered Outcomes Research Institute.

Attitude and preferences towards oral and long-acting injectable antipsychotics in patients with psychosis in KwaZulu-Natal, South Africa.

BackgroundPatient attitudes to and satisfaction with their treatment are associated with improved adherence. There is a paucity of data on patient drug attitudes and preference to oral compared to long-acting injectable (LAI) antipsychotic treatment.AimTo describe patients attitudes and preferences towards oral versus LAI antipsychotic formulations and explore factors associated with their drug attitudes.SettingTwo psychiatric hospitals in KwaZulu-Natal, South Africa.MethodA cross–sectional survey of 140 adult outpatients with schizophrenia spectrum disorders receiving LAI with or without oral antipsychotics (a total of 70) were compared to patients receiving oral antipsychotics only (N = 70). A sociodemographic-clinical questionnaire, chart review and the Drug Attitude Inventory scale (DAI–30) were used.ResultsOf the 140 participants, 98 (70%) preferred the medication formulation currently prescribed, and 132 (94.3%) reported a positive drug attitude towards their antipsychotic medication. The adjusted regression analysis indicated that study participants who were currently on a formulation that matched their preference scored better on the DAI-30 than individuals with a mismatch in use and preference (p < 0.04). In terms of covariates, we found, on one hand, that study participants who are divorced (compared to single) with schizophrenia diagnosis (compared to other psychotic or schizoaffective disorder) are more likely to have lower score on DAI-30. On the other hand, we found that study participants with a higher household income and longer duration of the psychotic illness were associated with greater DAI-30 score.ConclusionThe majority of participants preferred their current oral and LAI formulation. Drug attitude was influenced by several factors, including matched medication use. Focused psychoeducation should be considered for newly diagnosed, lower socio-economic groups and patients with non-affective psychosis to improve drug attitude.

Do Crude Oil Price Changes Affect Economic Welfare? Empirical Evidence from Ghana

Abstract&#x0D; This paper sought to explore the impact of crude oil price changes on economic welfare in Ghana. The paper employed the Autoregressive distributed lag (ARDL) estimation technique on an annual time series data spanning 1983 – 2017. The findings revealed that crude oil price changes have a negative and significant impact on economic welfare in the short and long run, albeit marginal. In terms of covariates, the findings revealed that trade openness and gross fixed capital formation have positive and significant impact whilst interest rate have negative impact on economic welfare in both the short and long run. Foreign direct investment had a positive effect, albeit insignificant. The paper recommends among others, the hedging of prices with respect to imported crude oil so as to manage the risks associated with crude oil price changes on economic welfare.&#x0D; &#x0D; Keywords: Economic Welfare; Crude Oil Prices Changes; Autoregressive Distributed Lag; Ghana

Development and growth of mohair fleeces from birth and relationships between skin follicle populations, mohair physical properties, animal size and fleece value

Abstract Knowledge of associations between skin follicle development in Angora goats and development of mohair fleeces is limited. These associations were investigated using data from a controlled nutrition experiment which had 3 levels of mid pregnancy nutrition (MPN) × 2 levels of postnatal nutrition during lactation (PNN), with single and twin litters. Skin biopsies were taken (birth, 114, 180, 420 days of age). Mid-side fibre growth and physical properties were determined 6 times between birth and 180 days of age. Birth coats were visually scored (1, straight; 5 curly). Fibre diameter distribution histograms were analysed at these ages. Skin area was measured. Total number of follicles and fibre growth per day determined. Fleeces were harvested at 7, 13 and 19 months of age and tested. Average fleece-free live weight (AvFFLwt) during fleece growing periods was determined. Data were analysed for treatment effects, correlations between attributes and multiple linear regression analysis performed to determine relationships between mean fibre diameter (MFD) at different ages with variables. AvFFLwt over the study within shearing intervals ranged from 5.8 to 37.6 kg. Density of secondary follicles (Ds) at 180 days of ranged from 10.8 to 34.0 mm−2, ratio of secondary to primary skin follicles (S/P) at 420 ranged from 4.8 to 14.1. Total fibre growth/day was related to the surface area (size) of kids, as surface area increased proportionally with live weight0.73. Smaller kids (female, twin reared) grew respectively 15–23% less fibre than larger male and 13–16% less than single reared goats. MFD was 27.8 μm at birth, then declined before increasing after 2 months of age. PNN had small effects on fibre diameter CV which was high at birth before declining rapidly during the first three months of life. There were negative correlations between both Ds and S/P ratio with: MFD; and the incidence of medullated fibres (patch fibre growth and fleeces at 13 and 19 months). The magnitude of these correlations increased with age. Birth coat score was negatively associated with fleece value. Predictions of MFD at shearing were related to log10AvFFLwt during the growth period, either Ds or S/P ratio, sex of kid, and a covariate term for the dam MFD. Greater Ds and S/P ratios greater than 9 were associated with finer mohair and more valuable fleeces.

Self-Concept in China: Validation of the Chinese Version of the Five-Factor Self-Concept (AF5) Questionnaire

The principle of invariance is a mandatory methodological requirement for the psychological measures, even when items such as self-concept measures frequently present asymmetric heavy-tailed distributions. Few validated self-concept instruments can be applied in Eastern–Western cross-cultural studies. The Five-Factor Self-Concept Questionnaire (AF5) is one of the few psychometrically sound instruments used to assess multidimensional self-concept in Spanish-speaking samples. The availability of the AF5 in Spanish and Chinese would facilitate cross-cultural research. To validate the Chinese version of the AF5, we used multisample confirmatory factor analysis with transformed dichotomous scales from the median to compare four alternative theoretical models. The sample consisted of 2507 participants (52.3% women) from China (n = 1298) and Spain (n = 1209), ranging in age from 19 to 35. Analyses confirmed the five-factor structure of the Chinese AF5 (i.e., academic, social, emotional, family, and physical) compared to the Spanish sample. Moreover, the Chinese version of the AF5 was found to be invariant in terms of item-factor weights, factor variance, and between-factor covariance, compared to the original Spanish version. The findings from this first validation study indicate that the Chinese version of the AF5 is an acceptable measure for use with Chinese-speaking adolescents and young adults.

PIN82 EXTENDING INFERENCES FROM A CLUSTER RANDOMIZED TRIAL TO A TARGET POPULATION

The clusters participating in cluster randomized trials are not necessarily representative of the target population of trial-eligible clusters where the experimental treatments might be applied. To the extent that participating and non-participating clusters differ in terms of covariates that are modifiers of the treatment effect, the average treatment effect in the trial may not apply to the entire target population. We describe analyses that extend (generalize or transport) causal inferences from cluster randomized trials to a target population of clusters, under a general nonparametric model that allows for arbitrary within-cluster dependence. We consider study designs where a subset of a cohort of clusters are invited and agree to participate in a randomized trial with cluster-level treatment assignment (i.e., nested trial designs). Treatment and outcome data need only be collected from clusters participating in the trial, but data on baseline covariates must be collected from the entire cohort. We propose doubly robust estimators of potential outcome means in the target population that exploit individual- level data on covariates and outcomes to improve efficiency and are appropriate for use with machine learning. We illustrate the methods using a 2x2 factorial cluster randomized trial of influenza vaccination strategies in 818 nursing homes that were nested in a cohort of 4,475 trial- eligible Medicare-certified nursing homes. We used machine learning methods to estimate the conditional probability of participation and the conditional probability of death, to obtain the potential outcome means for the vaccination strategies in the target population of trial-eligible nursing homes. Point estimates from generalizability analyses using different methods were similar, suggesting that the trial-only estimates were applicable to the broader population of trial-eligible nursing homes for the outcome of all-cause death. When cluster randomized trials are embedded in large health-care systems, investigators can use the methods to extend causal inferences.

Dynamic Analysis and State Estimation of Wearable Extra Robotic Limbs for Physical Assistance and Load Reduction in Missile-mounting

In order to fully exploit the potential in the field of human augmentation, to help the wearer fulfil the task of physical assistance and load reduction, a new type of wearable robot that can perform tasks in close coordination with the wearer and assist the wearer with extra arms and legs secured around the body is presented. The system, named extra auxiliary robotic upper limbs-lower extremity exoskeleton (EARUL-LEE), consists of two additional robotic arms worn through a backpack around the upper body and two exoskeleton legs attached to the lower body tightly. The EARUL-LEE can assist the wearer by holding objects, lifting weights and streamlining the execution of a task. If the EARUL-LEE performs movements closely coordinated with the wearer and exhibits human-like dynamics, it might be incorporated into the body representation and perceived as parts of the wearer’s body. The EARUL-LEE can work closely with the soldier by supporting and securing the human body when lifting a missile, and more. Although the EARUL-LEE control performance is hindered by unpredictable disturbances due to involuntary motions of the soldier, which include postural sway and physiological tremor, the dynamic analysis the human-EARUL-LEE hybrid system include the models of human-induced disturbance based on biomechanics literature, extra auxiliary robotic upper limbs and lower extremity exoskeleton and state estimation method based on an orthogonal least squares for the EARUL-LEE, aimed to perform the missile-mounting for aircrafts on the ground or decks in tight coordination with the soldier as a close co-worker are presented here. Via the current study, the orthogonal least squares (OLS) filter is constructed to estimate the state and its performance is evaluated in terms of error covariance. The simulation results show that the orthogonal least squares filter can tracking desired trajectory and its convergence is better than without any filters. The results can be used to control the EARUL-LEE accordingly with the used end effectors and provide a method for improving the accuracy and stabilizing the human body and the EARUL-LEE.