Error Variance Research Articles

The Internet Gaming Disorder Scale 9-Short Form: longitudinal measurement invariance across a three-year interval

ABSTRACT Objective Internet gaming disorder (IGD) refers to persistent, recurrent, and excessive involvement with computer or video games that cannot be controlled, despite associated problems. Given that it has been relatively stable for several years, questionnaires measuring IGD need to demonstrate measurement invariance (i.e. consistency in its measurement properties when administrated repeatedly over time), to ensure accurate measurement over time. This longitudinal study examined invariance of the Internet Gaming Disorder Scale 9-Short Form (IGDS9-SF5), which measures Internet gaming disorder (IGD) symptoms, based on the Diagnostic and Statistical Manual of Mental Disorders-5 criteria. Method Participants were recruited from English speaking countries (e.g. Australia, USA, UK and Canada). A total of 276 adults (mean age = 31.86 years; SD = 9.94; males = 71%) provided responses to an online survey (including demographic questions and the IGDS9-SF) at three time points one year apart (2020/21/22). Results When the chi-square difference (∆χ2) test was applied, the results supported configural invariance, full metric invariance, error variances, and invariance for all structural components (latent variances and covariances). However, scalar invariance was not observed for three item intercepts (tolerance, preoccupation, and giving up other activities). For all three items, the scores were higher at time 1 than time 2 and time 3. Conclusion The findings indicate that IGDS9-SF observed scores across yearly intervals are generally free from scaling and measurement biases, making them reliable for monitoring the progression of IGD symptoms and evaluating clinical treatment effects over time.

Assessing Balance of Baseline Time-Dependent Covariates via the Fréchet Distance.

Assessment of covariate balance is a key step when performing comparisons between groups particularly in real-world data. We generally evaluate it on baseline covariates, but rarely on longitudinal ones prior to a management decision. We could use pointwise standardized mean differences, standardized differences of slopes, or weights from the model for such purpose. Pointwise differences could be cumbersome for densely sampled longitudinal markers and/or measured at different points. Slopes are suitable for linear or transformable models but not for more complex curves. Weights do not identify the specific covariate(s) responsible for imbalances. This work presents the Fréchet distance as a viable alternative to assess balance of time-dependent covariates. A set of linear and nonlinear curves for which their standardized difference or differences in functional parameters were within 10% sought to identify the Fréchet distance equivalent to this threshold. This threshold is dependent on the level of noise present and thus within group heterogeneity and error variance are needed for its interpretation. Applied to a set of real curves representing the monthly trajectory of hemoglobin A1c from diabetic patients showed that the curves in the two groups were not balanced at the 10% mark. A Beta distribution represents the Fréchet distance distribution reasonably well in most scenarios. This assessment of covariate balance provides the following advantages: It can handle curves of different lengths, shapes, and arbitrary time points. Future work includes examining the utility of this measure under within-series missingness, within-group heterogeneity, its comparison with other approaches, and asymptotics.

Abstract TMP97: Association Between Race/Ethnicity and New Onset Atrial Fibrillation and Stroke Following Noncardiac Surgery

Background: Racial differences in postoperative atrial fibrillation (POAF) and stroke rates following noncardiac surgery are not well understood and may be influenced by varying betablocker prescription patterns. 1 Methods: This multicentric retrospective observational study included 205,886 adult patients without pre-existing atrial fibrillation who underwent non-cardiac surgery between 2005 and 2021 at two tertiary care academic healthcare networks in the Bronx, New York, and Boston, Massachusetts. The study population consisted of 133,500 (65%) Non-Hispanic White (NHW), 38,237 (19%) Non-Hispanic Black (NHB), and 34,149 (17%) Hispanic individuals. The exposure variable was self-identified race and ethnicity with NHW patients serving as the reference group. The incidence of POAF within 30 days of surgery and postoperative stroke within the first year after the procedure were assessed. Modified Poisson regression with robust error variances was used to evaluate the association between race/ethnicity and POAF and postoperative stroke, adjusting for pre-defined confounders. Mediation analysis was used to determine whether beta-blocker use modified the association between race/ethnicity and stroke. Results: NHB and Hispanic patients were less likely to develop POAF than NHW patients (NHB: RRadj = 0.59; 95%CI: 0.52-0.68; P < .001; Hispanic: RRadj = 0.65; 95%CI: 0.56-0.76; P < .001) but more likely to experience postoperative stroke (NHB: RRadj = 1.39; 95%CI, 1.30-1.49; P < .001; Hispanic: RRadj = 1.34; 95%CI, 1.24-1.46; P < .001). NHB and Hispanic patients were also more likely to be on preexisting beta-blocker therapy than NHW patients (NHB: RRadj = 1.10; 95%CI: 1.07-1.14; P < .001; Hispanic: RRadj = 1.07; 95%CI: 1.03-1.12; P < .001). Beta-blocker use was significantly associated with an increased risk of postoperative stroke (RRadj = 1.17; 95%CI: 1.11-1.24; P < .001) and explained 16% (95%CI: 14%-20%) and 20% (95%CI: 16%-26%) of the variability in postoperative stroke rates among NHB and Hispanic patients, respectively. Conclusion: NHB and Hispanic patients are at higher risk of developing postoperative stroke following noncardiac surgery compared to NHW patients, despite having a lower risk of POAF. This increased stroke risk may be partially attributable to the higher likelihood of preoperative beta-blocker prescriptions in these populations. Reference 1 - POISE Study Group. The Lancet. 2008 May 31;371(9627):1839-47.

P-1505. Impact of the Introduction of Ceftazidime-Avibactam in the Brazilian Market on Carbapenem and Ceftazidime-Avibactam Resistance in Klebsiella pneumoniae and Pseudomonas aeruginosa: Retrospective Analysis from 2017 to 2023

Abstract Background Bacterial resistance to carbapenems, poses a global health challenge, with Klebsiella pneumoniae and Pseudomonas aeruginosa as significant contributors. Ceftazidime-avibactam (CZA), introduced in Brazil in June 2018, offers a new treatment option for multi-resistant infections. However, increasing resistance to both this drug and carbapenems raises concerns. Our goal is to evaluate the impact of CZA introduction on resistance patterns, and metallo-betalactamases (MBL) prevalence in Brazil, focusing on K. pneumoniae and P. aeruginosa. Methods A retrospective analysis of microbiology data from a Private Laboratory (2017-2023) was conducted. Samples from 9 Brazilian states were assessed. We included all positive blood cultures and all resistant surveillance swab cultures for K. pneumoniae and P. aeruginosa. We excluded repeated positive blood cultures in a week interval with the same agent, and we considered only the first positive resistant surveillance culture. We considered carbapenem-resistant if the isolate was resistant to any carbapenem. It was evaluated phenotypically or genotypically and carbapenemase production patterns were aggregated into 3 categories: serine-, MBL, or co-production. We used Poisson regression model with a robust error variances variance to compare pre- and post-CZA introduction resistance prevalences. The models were adjusted for COVID-19 national incidence, age, and gender. Results We analyzed 9361 positive blood and 16862 carbapenem-resistant surveillance cultures. In blood cultures, CZA resistance rose after its introduction in K. pneumoniae (3% to 9%; 2019 to 2023 (p < 0.001), so did the MBL production (0% to 6%, p 0.02), and serine- and MBL co-production: 0% to 1% (p 0.04). MBL also increased in P. aeruginosa during the study period: 0% to 4% from 2017 to 2023 (p < 0.001). In surveillance cultures, carbapenemase production increased in P. aeruginosa after CZA introduction: 5% to 22%, p < 0.001. Conclusion The observed increases in resistance prevalence and carbapenemase production associated with CZA introduction indicate limitations for its use. Enhanced surveillance and antimicrobial stewardship strategies are urgently needed to address the growing threat of antimicrobial resistance. Disclosures All Authors: No reported disclosures

An interval robust optimization with maximum input tolerance for engineering design

Most existing robust optimization (RO) methods for engineering design consider parameter design and tolerance design as separate design phases. This study is to develop an interval RO strategy for engineering design realizing the approval maximum input tolerance with robustness guaranteed. Taking the errors of design variables into account, an interval RO model based on dimensional tolerance or geometrical tolerance is constructed to optimize the nominal values and tolerances of design variables simultaneously. In the constructed model, the interval midpoint and radius of the concern performance are used to evaluate the robustness, and the overall uncertainties of all design variables are quantified by integrating a dimensionless tolerance index. And then, through the reliability-based possibility degree of interval to cope with uncertain constraints it can be converted into a deterministic multi-objective optimization problem. Finally, the deterministic multi-objective optimization problem is treated by a developed robust multi-objective genetic algorithm. The results and the potential of the proposed model and method are illustrated by the numerical and engineering examples.

A novel filtering-based recursive identification method for a fractional-order Hammerstein state space system with piecewise nonlinearity

This paper investigates parameters and states estimation for a class of fractional-order state space systems with colored noises. To provide accurate parameter estimation, we suggest a novel gradient descent algorithm based on the extended Kalman filtering. The new approach features lower estimation error variances and a faster convergence rate than the conventional gradient descent algorithm. A data filtering is introduced to filter the input and output data, thereby reducing the impact of colored noises on the accuracy of the parameter estimates.

Performance Assessment of a Coupled Circulation–Wave Modelling System for the Northwest Atlantic

We present a modified version of a coupled circulation–wave modelling system for the northwest Atlantic (CWMS-NWA) by including additional physics associated with wave–current interactions. The latest modifications include a parameterization of Langmuir turbulence and surface flux of turbulent kinetic energy from wave breaking in vertical mixing. The performance of the modified version of CWMS-NWA during Hurricane Arthur in 2014 is assessed using in situ measurements and satellite data. Several error statistics are used to evaluate the model performance, including correlation (R), root mean square error (RMSE), normalized model variance of model errors (γ2) and relative bias (RB). It is found that the simulated surface waves (R ≈ 94.0%, RMSE ≈ 27.5 cm, γ2≈ 0.16) and surface elevations (R ≈ 97.3%, RMSE ≈ 24.0 cm, γ2≈ 0.07) are in a good agreement with observations. The large-scale circulation, hydrography and associated storm-induced changes in the upper ocean during Arthur are reproduced satisfactorily by the modified version of CWMS-NWA. Relative to satellite observations of the daily averaged sea surface temperature (SST), the model reproduces large-scale features as demonstrated by the error metrics: R ≈ 97.8%, RMSE ≈ 1.6 ∘C and RB ≈ 8.6 ×10−3∘C.

Representational geometry explains puzzling error distributions in behavioral tasks

Measuring and interpreting errors in behavioral tasks is critical for understanding cognition. Conventional wisdom assumes that encoding/decoding errors for continuous variables in behavioral tasks should naturally have Gaussian distributions, so that deviations from normality in the empirical data indicate the presence of more complex sources of noise. This line of reasoning has been central for prior research on working memory. Here, we reassess this assumption and find that even in ideal observer models with Gaussian encoding noise, the error distribution is generally non-Gaussian, contrary to the commonly held belief. Critically, we find that the shape of the error distribution is determined by the geometrical structure of the encoding manifold via a simple rule. In the case of a high-dimensional geometry, the error distributions naturally exhibit flat tails. Using this insight, we apply our theory to visual short-term memory tasks, and find that it can account for a large array of experimental data with only two free parameters. Our results challenge the dominant view in the mechanisms and capacity constraints of working memory systems. They instead suggest that the Bayesian framework, which explains various aspects of perceptual behavior, also provides an excellent account of working memory. Overall, our results establish a direct connection between neural manifold geometry and behavior, and call attention to the geometry of the representation as a critically important, yet underappreciated factor in determining the character of errors in human behavior.

Assessing the transmission of global market volatility to Moroccan food prices: a VECM-based analysis with forecast error variance decomposition

PurposeThis paper examines the transmission of global food (GF) and global energy (GE) volatilities to the Moroccan food market, focusing on both aggregated and specific commodities such as dairy, meat and oils and fats.Design/methodology/approachUsing monthly data from September 2009 to June 2024, a vector error correction model (VECM) was estimated to capture short-run and long-run dynamics. The analysis is complemented by impulse response functions (IRFs) and forecast error variance decomposition (FEVD) to provide insights into the transmission mechanisms.FindingsThe results indicate an increased sensitivity of the Moroccan food market, particularly following the 2021 price spikes. The study identifies energy input costs, particularly related to fertilizers and transportation, as primary transmission mechanisms. Additionally, the real effective exchange rate (REER) also significantly influences the Moroccan food market.Research limitations/implicationsFurther research could explore the transmission from oil derivatives, such as gasoline and fuel, which are directly used in agricultural activities, to provide a more comprehensive understanding.Social implicationsUnderstanding the transmission of global shocks to domestic markets can help in developing strategies to enhance food security and protect consumers from price volatility.Originality/valueThis study contributes to the literature by comprehensively analyzing the direct and indirect transmission mechanisms from global food and energy markets to the Moroccan food market, with policy implications to enhance price stability.

Research on a Density-Based Clustering Method for Eliminating Inter-Frame Feature Mismatches in Visual SLAM Under Dynamic Scenes

Visual SLAM relies on the motion information of static feature points in keyframes for both localization and map construction. Dynamic feature points interfere with inter-frame motion pose estimation, thereby affecting the accuracy of map construction and the overall robustness of the visual SLAM system. To address this issue, this paper proposes a method for eliminating feature mismatches between frames in visual SLAM under dynamic scenes. First, a spatial clustering-based RANSAC method is introduced. This method eliminates mismatches by leveraging the distribution of dynamic and static feature points, clustering the points, and separating dynamic from static clusters, retaining only the static clusters to generate a high-quality dataset. Next, the RANSAC method is introduced to fit the geometric model of feature matches, eliminating local mismatches in the high-quality dataset with fewer iterations. The accuracy of the DSSAC-RANSAC method in eliminating feature mismatches between frames is then tested on both indoor and outdoor dynamic datasets, and the robustness of the proposed algorithm is further verified on self-collected outdoor datasets. Experimental results demonstrate that the proposed algorithm reduces the average reprojection error by 58.5% and 49.2%, respectively, when compared to traditional RANSAC and GMS-RANSAC methods. The reprojection error variance is reduced by 65.2% and 63.0%, while the processing time is reduced by 69.4% and 31.5%, respectively. Finally, the proposed algorithm is integrated into the initialization thread of ORB-SLAM2 and the tracking thread of ORB-SLAM3 to validate its effectiveness in eliminating feature mismatches between frames in visual SLAM.

Use of patient portals to disclose STI test histories to sex partners among U.S. men who have sex with men: A call for research and guidance.

This study investigates the use of patient portals for disclosing sexually transmitted infection (STI) test result histories to sexual partners among men who have sex with men (MSM) in the United States. Using data from the 2022-2023 American Men's Internet Survey, this cross-sectional analysis examined demographic, behavioral, and healthcare-related factors associated with MSM's utilization of patient portals for sharing STI test results. Participants (N = 2601) were surveyed on portal use, STI testing frequency, and partner disclosure practices. 18% of survey participants used portals to disclose a STI test result to parrtners, with higher prevalences among individuals aged 16-37 years old versus 56 years and older, black non-Hispanic (26.4%) versus white non-Hispanic (16.8%), and those reporting nine or more times being tested for STIs (30.1%) versus 1 to 3 times (7.5%). Participants reporting sex work (33.3% vs 17.7%) and HIV pre-exposure prophylaxis (PrEP) use (24.2% vs 13.0%) also had a higher prevalence of portal use for disclosure. Multivariable Poisson regression analysis with robust error variance showed that sexual behavioral stigma from family and friends [adjusted prevalence ratio (aPR) = 1.11; p = .04] also, being tested for STIs four to 8 (aPR = 2.21; p < .001) and nine or more times aPR = 3.42; p < .001) were significantly associated with prevalence of portal-based disclosure. Findings suggest patient portals may be viable tools for STI prevention in MSM communities, especially among individuals with increased vulnerability to STI acquisition. Addressing disparities in portal access and explaining patient portal capabilities may enhance the role of digital health in reducing STI transmission among MSM communities.

Increasing certainty in projected local extreme precipitation change

The latest climate models project widely varying magnitudes of future extreme precipitation changes, thus impeding effective adaptation planning. Many observational constraints have been proposed to reduce the uncertainty of these projections at global to sub-continental scales, but adaptation generally requires detailed, local scale information. Here, we present a temperature-based adaptative emergent constraint strategy combined with data aggregation that reduces the error variance of projected end-of-century changes in annual extremes of daily precipitation under a high emissions scenario by >20% across most areas of the world. These improved projections could benefit nearly 90% of the world’s population by permitting better impact assessment and adaptation planning at local levels. Our physically motivated strategy, which considers the thermodynamic and dynamic components of projected extreme precipitation change, exploits the link between global warming and the thermodynamic component of extreme precipitation. Rigorous cross-validation provides strong evidence of its reliability in constraining local extreme precipitation projections.

Validation of the Maslach burnout inventory-general survey 9-item short version (MBI-GS9) among care aides in Canadian nursing homes

BackgroundThe Maslach Burnout Inventory-General Survey (MBI-GS) is the leading measure of burnout for all occupations. The MBI-GS9, the 9-item version of the MBI-GS, was formulated based on the MBI-GS and has been used for several years. However, very few studies have systematically tested its psychometric properties, and none have focused on care aides working in nursing homes who are susceptible to burnout.MethodsFollowing the Standards for Educational and Psychological Testing, this study validated the MBI-GS9 among 3,765 care aides from 91 Canadian nursing homes, using data collected between September 2019 and February 2020 by the Translating Research in Elder Care (TREC) program.ResultsThe Exhaustion subscale had good reliability with coefficients around 0.66–0.74. The Cynicism subscale had medium reliability with coefficients around 0.60–0.66, and the Efficacy subscale also had medium reliability with coefficients around 0.51–0.58. The MBI-GS9 was significantly correlated with various conceptually related constructs, such as health status, working environment, job satisfaction, psychological empowerment, work engagement, and organizational citizenship behaviors. The MBI-GS9 had a three-factor structure in the full sample and showed equivalent factor structure, factor loadings, latent values, factor variance and error variance across different sex and age groups. Care aides with English as their first language showed higher latent values of the Exhaustion subscale compared to those with English as a second language.ConclusionOverall, the MBI-GS9 exhibited acceptable psychometric properties, but medium reliability of cynicism and efficacy subscales, for measuring burnout among care aides in nursing homes, demonstrating equivalence across sex and gender groups. When comparing across different languages or racial or ethnic groups among care aides, it is important to consider inequivalent latent values on Exhaustion before comparing scores on the measure.

Error analysis for the implicit boundary integral method

The implicit boundary integral method (IBIM) provides a framework to construct quadrature rules on regular lattices for integrals over irregular domain boundaries. This work provides a systematic error analysis for IBIMs on uniform Cartesian grids for boundaries with different degrees of regularity. First, it is shown that the quadrature error gains an additional order of d-12 from the curvature for a strongly convex smooth boundary due to the “randomness” in the signed distances. This gain is discounted for degenerated convex surfaces. Then the extension of error estimate to general boundaries under some special circumstances is considered, including how quadrature error depends on the boundary’s local geometry relative to the underlying grid. Bounds on the variance of the quadrature error under random shifts and rotations of the lattices are also derived.

Immediate skin-to-skin contact and postpartum hemorrhagic morbidity.

To examine rates of postpartum hemorrhagic (PPH) morbidity among patients who did and did not have immediate skin-to-skin contact (SSC). This study was a retrospective cohort of all non-anomalous, term singleton vaginal births at a Level IV center over 2 years. Exclusion criteria included COVID-19. Immediate SSC was defined as at least 60 min of direct contact initiated between parturient and neonate within 10 min of birth. The primary outcome was a composite of maternal morbidity related to PPH compared among those with and without immediate SSC. We used multivariable Poisson regression adjusted for possible confounders with robust error variance to determine the strength of the association. Of 8623 deliveries during the study period, 3520 (40.8%) deliveries were included; of which 2428 (55.5%) had immediate SSC and 1028 (31.0%) did not. Immediate SSC reduced the overall rate of composite morbidity (adjusted relative risk 0.78, 95% confidence interval 0.65-0.92), and rate of blood loss 1000 mL or greater, use of additional uterotonics, and use of mechanical tamponade. Blood loss and third stage of labor duration were significantly less for immediate SSC. Transfusion rate and hematocrit change after delivery, did not differ. Immediate SSC among term vaginal deliveries was associated with a significant reduction in PPH. Emphasis on early contact for maternal benefit may increase uptake of SSC and provide an accessible intervention for PPH in high- and low-resource settings.

Observer-based adaptive control for fractional-order strict-feedback nonlinear systems with state quantisation and input quantisation

This paper investigates the adaptive control problems of fractional-order strict-feedback nonlinear systems with state quantisation and input quantisation. Both Caputo and Riemann–Liouville derivative definitions are considered. Based on these two definitions, two fractional-order state observers are constructed to smooth the discontinuous quantised states, respectively. Then, new error variables and the dynamic filters are introduced to facilitate the design of the adaptive quantised controller. It is shown that the designed controller is valid for fractional-order strict-feedback nonlinear systems under both Caputo derivative definition and Riemann–Liouville derivative definition. Finally, three examples are given to demonstrate the effectiveness of the proposed method.

What explains monetary policy rate uncertainty? Evidence from the Americas

ABSTRACT Using Consensus Forecasts for 8 American countries, we compute uncertainty regarding outcomes based on the sum of disagreement across forecasters and the error variance of the mean forecaster. Uncertainty for inflation and monetary policy tend to move together. This is consistent with economic forecasters using a Taylor rule to form their expectations and believing that central bankers put a high weight on inflation deviations. We find that monetary policy rate uncertainty in the short term (12 months ahead) is strongly associated with higher uncertainty regarding the inflation rate in the next year. The result is significant across all countries in the medium term. Inflation uncertainty is a much more powerful predictor of monetary policy uncertainty than GDP growth uncertainty in the medium term. Furthermore, the post-pandemic years are the first period in the twenty-first century in which uncertainty for monetary policy and inflation surged across all countries. The post-pandemic period saw a significant reduction in GDP growth uncertainty across all countries (except Argentina), but this was not enough to attenuate the increase in inflation and monetary policy uncertainty.

Determinants of Severe Hypocalcemia After Parathyroidectomy in Patients with End-Stage Kidney Disease and Renal Hyperparathyroidism: A Retrospective Cohort Study.

Background: Parathyroidectomy (PTX) is generally curative in renal hyperparathyroidism (RHPT) that is refractory to medical treatment in end-stage kidney disease (ESKD) patients. Severe hypocalcemia is a common complication of PTX and results in increased monitoring, interventions, lengths of stay, and costs of care. This study aimed to find the determinants and cutoff values of the biochemical determinants, if any, for severe post-operative hypocalcemia after PTX in adult patients with ESKD. Methods: Severe post-operative hypocalcemia was defined as a lowest adjusted serum calcium level < 2 mmol/L during a hospitalization stay following PTX. Receiver operating curves (ROCs) with area under the curve (AUC) values for pre-operative intact parathyroid hormone (iPTH) and pre-operative alkaline phosphatase (ALP) levels against hypocalcemia were used to determine cutoffs. Generalized linear models using Poisson regression with robust error variance were used to estimate the relative risk of severe post-operative hypocalcemia. Results: In total, 75 patients (38 women, 50.7%) with a mean age of 53.8 ± 11.4 years were enrolled; 43 (57%) patients developed severe hypocalcemia post-PTX and had higher pre-operative serum iPTH and ALP levels, as well as a significantly longer hospitalization post-operation (10.5 vs. 4.3 days, p =< 0.001). A pre-operative iPTH level of >166 pmol/L had an AUC-ROC of 0.73 and 72% sensitivity and 73% specificity, respectively, in predicting severe post-operative hypocalcemia with a relative risk of 2.00 [95% CI 1.27-3.33, p = 0.003]. Conclusions: A pre-operative iPTH level > 166 pmol/L is a strong risk predictor for post-operative severe hypocalcemia. Pre-emptive interventions in this high-risk group could potentially result in a reduced length of stay and lower acuity of care.

Character Association and Path Analysis of Garlic (Allium sativum L.) for Yield and Its Attributes

This research sought to determine the associations between bulb yield and other traits and to measure their effects of yield attributes on bulb yield of garlic genotypes. The experiment was laid out in randomized complete block design (RCBD) with three replications using twenty garlic genotypes with one standard check variety (HL) at Kulumsa Agricultural Research center, during 2020-2021. Yield and agronomic traits were determined. The data from two years were analyzed separately because the homogeneity of error variances of both seasons were not similar. In both seasons the association analyses indicated that the bulb yield was positively and significantly associated with plant vigor (0.9762), plant height (0.9057), neck thickness (0.5918), leaf width (0.7527), number of clove per bulb (0.766), cloves weight (0.9621), bulb polar diameter (0.9247), pseudo stem length (0.7885), clove height (0.9161), clove diameter (0.6412). Days to maturity and leaf length were negatively correlated with bulb yield at genotypic and phenotypic level. Consequences of path analyses indicated that bulb polar diameter (1.2478), clove height (1.0911), clove weight (0.9621), plant height (0.9057) and plant vigor (0.9762) had the highest positive direct effect on bulb yield at genotype level in first season and number of clove per bulb (0.9971), leaf width (0.9126), neck thickness (0.9912) in the 20221 season. On the other hand, most of the indirect effects of yield components on bulb yield were significant and positive. Because of the significant direct effects and positive correlations of those traits on bulb yield at phenotypic and genotypic levels, may be observed as important traits for garlic genotypes selection programs.

Test for Change in Error Variance of Multiple Time Series

Changes in levels of multiple time series based on their common components helps characterize the shared behavior of the data generating process with known events causing perturbations in their movements. However, changes in variance of the error structure leads to misspecification of models that complicates statistical inference. Volatility structures may incorporate variance into the time series models, but these can easily lead to overparameterization in multiple time series. A model with inherent changes in variance structure is used to develop a bootstrap-based test for presence of changes in variance of multiple time series. Simulation studies shows that the test is correctly-sized and powerful compared to CUSUM-based test in a wide range of scenarios. The test is advantageous specially in the presence of strong autocorrelations and even in unbalanced data. Using global stock prices with the onset of lockdowns against the COVID19 pandemic as the stimulus of the changepoint, the test was able to detect significant changes in error variance before and during the pandemic. While CUSUM-based test also recognized the significant changes in multiple time series, linear trend was misconstrued as evidence of the presence of change in variance in stock prices.