Wald Test Research Articles

SARS-CoV-2 infection is associated with an increase in new diagnoses of schizophrenia spectrum and psychotic disorder: A study using the US national COVID cohort collaborative (N3C).

Amid the ongoing global repercussions of SARS-CoV-2, it is crucial to comprehend its potential long-term psychiatric effects. Several recent studies have suggested a link between COVID-19 and subsequent mental health disorders. Our investigation joins this exploration, concentrating on Schizophrenia Spectrum and Psychotic Disorders (SSPD). Different from other studies, we took acute respiratory distress syndrome (ARDS) and COVID-19 lab-negative cohorts as control groups to accurately gauge the impact of COVID-19 on SSPD. Data from 19,344,698 patients, sourced from the N3C Data Enclave platform, were methodically filtered to create propensity matched cohorts: ARDS (n = 222,337), COVID-19 positive (n = 219,264), and COVID-19 negative (n = 213,183). We systematically analyzed the hazard rate of new-onset SSPD across three distinct time intervals: 0-21 days, 22-90 days, and beyond 90 days post-infection. COVID-19 positive patients consistently exhibited a heightened hazard ratio (HR) across all intervals [0-21 days (HR: 4.6; CI: 3.7-5.7), 22-90 days (HR: 2.9; CI: 2.3 -3.8), beyond 90 days (HR: 1.7; CI: 1.5-1.)]. These are notably higher than both ARDS and COVID-19 lab-negative patients. Validations using various tests, including the Cochran Mantel Haenszel Test, Wald Test, and Log-rank Test confirmed these associations. Intriguingly, our data indicated that younger individuals face a heightened risk of SSPD after contracting COVID-19, a trend not observed in the ARDS and COVID-19 negative groups. These results, aligned with the known neurotropism of SARS-CoV-2 and earlier studies, accentuate the need for vigilant psychiatric assessment and support in the era of Long-COVID, especially among younger populations.

Estimation and hypothesis test for varying coefficient single-index multiplicative models

ABSTRACT Estimation and hypothesis test for varying coefficient single-index multiplicative models are considered in this paper. To estimate an unknown single-index parameter, a profile product relative error estimation is proposed for the single-index parameter with a leave-one-component-out estimation method. A Wald-type test statistic is proposed to test a linear hypothesis test of the single-index. We employ the smoothly clipped absolute deviation penalty to simultaneously select variables and estimate regression coefficients. To study the model checking problem, we propose a variant of the integrated conditional moment test statistic by using a linear projection weighting function, and we also suggest a bootstrap procedure for calculating critical values. Simulation studies are conducted to demonstrate the performance of the proposed procedure and a real example is analysed for illustration.

Indivudual and implant factors associeated with peri-implantitis: a multi-level analysis

The study aimed to carry out a multilevel analysis of the factors associated with peri-implantitis in patients who were rehabilitated with osseointegrated implants at the Dental Clinic of Universidade Paulista (UNIP). Being analyzed by means of influence on the patients' quality of life, 171 patients with 668 implants, with 5 years in function, were selected through clinical and radiographic examinations. Systemic and local factors and characteristics were evaluated to determine the health of the peri-implant tissues. Quality of life was assessed using the Oral Health Impact Profile Index (OHIP-14). Multilevel logistic analysis was performed to estimate the OR of peri-implantitis at implant and patient level. The model was analyzed using the likelihood ratio test and the Wald test. Through the results, it was verified that the probing depth both at the implant and patient level and the distance from the gingival margin to the implant platform are factors risk for peri-implantitis. However, due to the low prevalence of the disease, there was no negative impact on the patients' quality of life.

Frailty, but not cognitive impairment, improves mortality risk prediction among those with chronic kidney disease-a nationally representative study.

Though older adults with chronic kidney disease (CKD) have a greater mortality risk than those without CKD, traditional risk factors poorly predict mortality in this population. Therefore, we tested our hypothesis that two common geriatric risk factors, frailty and cognitive impairment, and their co-occurrence, might improve mortality risk prediction in CKD. Among participants aged ≥ 60years from National Health and Nutrition Examination Survey (2011-2014), we quantified associations between frailty (physical frailty phenotype) and global/domain-specific cognitive function (immediate-recall [CERAD-WL], delayed-recall [CERAD-DL], verbal fluency [AF], executive function/processing speed [DSST], and global [standardized-average of 4 domain-specific tests]) using linear regression, and tested whether associations differed by CKD using a Wald test. We then tested whether frailty, global cognitive impairment (1.5SD below the mean), or their combination improved prediction of mortality (Cox models, c-statistics) compared to base models (likelihood-ratios) among those with and without CKD. Among 3,211 participants, 1.4% were cognitively impaired, and 10.0% were frail; frailty and cognitive impairment co-occurrence was greater among those with CKD versus those without (1.2%vs.0.1%). Frailty was associated with worse global cognitive function (Cohen's d = -0.26SD,95%CI -0.36,-0.17), and worse cognitive function across all domains; these associations did not differ by CKD (pinteractions > 0.05). Mortality risk prediction improved only among those with CKD when accounting for frailty (p[likelihood ratio test] < 0.001) but not cognitive impairment. Frailty is associated with worse cognitive function regardless of CKD status. While CKD and frailty improved mortality prediction, cognitive impairment did not. Risk prediction tools should incorporate frailty to improve mortality prediction among those with CKD.

Covariance structure tests for multivariate t-distribution

We derive an equation system for finding Maximum Likelihood Estimators (MLEs) for the parameters of a p-dimensional t-distribution with ν\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ u $$\\end{document} degrees of freedom, tp,ν\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$t_{p,\ u }$$\\end{document}, and use the MLEs for testing covariance structures for the tp,ν\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$t_{p,\ u }$$\\end{document}-distributed population. The likelihood ratio test (LRT), Rao score test (RST) and Wald test (WT) statistics are derived under the general null-hypothesis H0:Σ=Σ0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{H}_0:\\varvec{\\Sigma }=\\varvec{\\Sigma }_0$$\\end{document}, using a matrix derivative technique. Here the p×p\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p\ imes p$$\\end{document}-matrix Σ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varvec{\\Sigma }$$\\end{document} is a dispersion/scale parameter. Convergence to the asymptotic chi-square distribution under the null hypothesis is examined in extensive simulation experiments. Also the convergence to the chi-square distribution is studied empirically in the situation when the MLEs of a tp,ν\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$t_{p,\ u }$$\\end{document}-distribution are changed to the corresponding estimators for a normal population. Type I errors and the power of the tests are also examined by simulation. In the simulation study the RST behaved more adequately than all remaining statistics in the situation when the dimensionality p was growing.

Differences in Racial and Ethnic Disparities Between First and Repeat Kidney Transplantation.

Recent data suggest patients with graft failure had better access to repeat kidney transplantation (re-KT) than transplant-naive dialysis accessing first KT. This was postulated to be because of better familiarity with the transplant process and healthcare system; whether this advantage is equitably distributed is not known. We compared the magnitude of racial/ethnic disparities in access to re-KT versus first KT. Using United States Renal Data System, we identified 104 454 White, Black, and Hispanic patients with a history of graft failure from 1995 to 2018, and 2 357 753 transplant-naive dialysis patients. We used adjusted Cox regression to estimate disparities in access to first and re-KT and whether the magnitude of these disparities differed between first and re-KT using a Wald test. Black patients had inferior access to both waitlisting and receiving first KT and re-KT. However, the racial/ethnic disparities in waitlisting for (adjusted hazard ratio [aHR] = 0.77; 95% confidence interval [CI], 0.74-0.80) and receiving re-KT (aHR = 0.61; 95% CI, 0.58-0.64) was greater than the racial/ethnic disparities in first KT (waitlisting: aHR = 0.91; 95% CI, 0.90-0.93; Pinteraction = 0.001; KT: aHR = 0.68; 95% CI, 0.64-0.72; Pinteraction < 0.001). For Hispanic patients, ethnic disparities in waitlisting for re-KT (aHR = 0.83; 95% CI, 0.79-0.88) were greater than for first KT (aHR = 1.14; 95% CI, 1.11-1.16; Pinteraction < 0.001). However, the disparity in receiving re-KT (aHR = 0.76; 95% CI, 0.72-0.80) was similar to that for first KT (aHR = 0.73; 95% CI, 0.68-0.79; Pinteraction = 0.55). Inferences were similar when restricting the cohorts to the Kidney Allocation System era. Unlike White patients, Black and Hispanic patients with graft failure do not experience improved access to re-KT. This suggests that structural and systemic barriers likely persist for racialized patients accessing re-KT, and systemic changes are needed to achieve transplant equity.

Resilience in the first year of surviving a stroke in Nigeria

Objectives There is a knowledge gap on resilience and its impact on mental health of Africans who survive a stroke. We describe the trajectory of psychological resilience and its association with depression and quality of life (QoL) across the first poststroke year in Nigeria. Method Prospective observational study of 150 survivors of a first ever stroke. Resilience was ascertained at 3 time-points prospectively over 12 months using the 25-items Resilience Scale (RS). Depression and QoL were also assessed at baseline and follow-up, respectively using the centre for epidemiologic studies depression scale (CES-D 10) and health related quality of life in stroke patients (HRQOLISP-26). Associations were investigated using regression models and presented as adjusted odds ratios (OR) and Wald test coefficients within 95% confidence intervals (CI). Results Resilience improved across time points of measurement (p < 0.001). In multivariate logistic regression analyses adjusted for the effect of age, education, alcohol use, and hypertension, higher resilience was associated with male sex (OR = 5.3, 95% CI= 1.7, 17.2), younger age (OR = 4.8, 95% CI = 1.5,15.7), and baseline hypertension (OR= 0.2, 95% CI ≤ 0.1,0.8). In similarly adjusted mixed effect linear regression analyses, higher resilience was associated with improvement in depression (months 12= −4.2, 95% CI= −5.6, −2.8) and quality of life (months twelve = 5.2, 95% CI = 2.2, 8.2) overtime. Conclusion Resilience, which was associated with better mental health and wellbeing of stroke survivors, was less likely with hypertension. Results suggest an important role for control of vascular risk factors as part of resilience interventions to promote poststroke recovery.

Tricks with metrics: combining statistics for improved inference in regression analysis

. In maximum likelihood methods, the three classical tests statistics are often unreliable for inference in small samples, even under the correct model specification. In this article, I discuss how likelihood ratio and Wald test statistics can be combined to obtain highly improved parameter inference in regression models with small samples. I consider modifications obtained from both the Barndorff-Nielsen and the Lugannani and Rice likelihood approximations, and I show how they can produce highly accurate parameter inference in a general (possibly non linear) regression model with possibly non spherical disturbances. I discuss the underlying theory and provide Monte Carlo simulations demonstrating the superior accuracy of the proposed procedures over the first-order classical likelihood methods (i.e., the signed log-likelihood ratio test and the Wald test). An empirical application to a regression model of mobile money (“M-pesa”) adoption in Kenya is provided as an illustration of the usefulness of these methods in practice.

Sample size calculation for comparing two screening tests when the gold standard is missing at random.

Sample size formulas have been proposed for comparing two sensitivities (specificities) in the presence of verification bias under a paired design. However, the existing sample size formulas involve lengthy calculations of derivatives and are too complicated to implement. In this paper, we propose alternative sample size formulas for each of three existing tests, two Wald tests and one weighted McNemar's test. The proposed sample size formulas are more intuitive and simpler to implement than their existing counterparts. Furthermore, by comparing the sample sizes calculated based on the three tests, we can show that the three tests have similar sample sizes even though the weighted McNemar's test only use the data from discordant pairs whereas the two Wald tests also use the additional data from accordant pairs.

Effect of Corporate Environmental Performance on Banks’ Loan Pricing

Effect of Corporate Environmental Performance on Banks’ Loan Pricing

Economic Growth Effects of Fiscal Policy in South Africa: Empirical Evidence from Personal Income Tax

Economic Growth Effects of Fiscal Policy in South Africa: Empirical Evidence from Personal Income Tax

Differences In Quality of Life of Nasopharyngeal Carcinoma Patients at Rsi Sultan Agung Semarang Observational Analytical Studies in Age, Gender, and Stage of Cancer

Nasopharyngeal carcinoma is a malignant tumor in the head and neck area of squamous cell type located in the nasopharynx. Nasopharyngeal carcinoma in Indonesia is the 4th most malignant cancer and is considered one of the most malignant tumors with high mortality and morbidity. This study aims to determine the difference in quality of life in nasopharyngeal carcinoma patients with characteristics (age, gender, and stage of cancer) nasopharyngeal tumors. The research method was carried out with analytical observational through a cross sectional approach. The measuring instruments used in the form of EORTC QLQ-C30 and EORTC QLQ-H&amp;N35 questionnaires were used to measure the quality of life of nasopharyngeal carcinoma patients at RSI Sultan Agung Semarang. The data were analyzed using a binary logistic regression test. The results of the study of nasopharyngeal carcinoma patients according to the characteristics at RSI Sultan Agung Semarang based on 13 respondents were dominated by male patients totaling 8 people (61.54%), aged 45 years as many as 8 people (61.54%), and cancer stages were divided into 6 people (≥46.15%) and 7 people (53.85%) in the early and advanced stages. The results of the Wald Test did not significantly differ in the quality of life of nasopharyngeal carcinoma patients at RSI Sultan Agung Semarang with each sig intention. The independent variables were age (p = 0.187), gender (p = 0.227), and cancer stage (p = 0.558). The independent variable that most affected the level of quality of life of nasopharyngeal carcinoma patients was gender with a value of Exp(B) = 5.394. The conclusion of this study is that there is no difference in quality of life in nasopharyngeal carcinoma patients with characteristics (age, gender, and stage of cancer) nasopharyngeal tumors.International Journal of Human and Health Sciences Vol. 08 No. 02 Apr’24 Page: 151-156

Reprint of: The likelihood ratio test for structural changes in factor models

A factor model with a break in its factor loadings is observationally equivalent to a model without changes in the loadings but with a change in the variance of its factors. This approach effectively transforms a high-dimensional structural change problem into a low-dimensional problem. This paper considers the likelihood ratio (LR) test for a variance change in the estimated factors. The LR test implicitly explores a special feature of the estimated factors: the pre-break and post-break variances can be a singular matrix under the alternative hypothesis, making the LR test diverging faster and thus more powerful than Wald-type tests. The better power property of the LR test is also confirmed by simulations. We also consider mean changes and multiple breaks. We apply this procedure to the factor modeling of the US employment and study the structural change problem using monthly industry-level data.

Prediagnostic plasma proteomics profile for hepatocellular carcinoma.

Proteomics may discover pathophysiological changes related to hepatocellular carcinoma, an aggressive and lethal type of cancer with low sensitivity for early stage diagnosis. We measured 1305 prediagnostic (median = 12.7 years) SomaScan proteins from 54 pairs of healthy individuals who subsequently developed hepatocellular carcinoma and matched non-hepatocellular carcinoma control individuals from the Nurses' Health Study (NHS) and the Health Professionals Follow-up Study (HPFS). Candidate proteins were validated in the independent, prospective UK Biobank Pharma Proteomics Project (UKB-PPP). In NHS and HPFS, we identified 56 elevated proteins in hepatocellular carcinoma with an absolute fold change of more than 1.2 and a Wald test P value less than .05 in conditional logistic regression analysis. Ingenuity pathway analysis identified enrichment of pathways associated with cell viability, adhesion, proteolysis, apoptosis, and inflammatory response. Four proteins-chitinase-3-like protein 1, growth differentiation factor 15, interleukin-1 receptor antagonist protein, and E-selectin-showed strong positive associations with hepatocellular carcinoma and were thus validated by enzyme-linked immunosorbent assay (odds ratio = 2.48-14.7, all P < .05) in the NHS and HPFS and by Olink platform (hazard ratio = 1.90-3.93, all P < .05) in the UKB-PPP. Adding these 4 proteins to a logistic regression model of traditional hepatocellular carcinoma risk factors increased the area under the curve from 0.67 to 0.87 in the NHS and HPFS. Consistently, model area under the curve was 0.88 for hepatocellular carcinoma risk prediction in the UKB-PPP. However, the limited number of hepatocellular carcinoma patients in the cohorts necessitates caution in interpreting our findings, emphasizing the need for further validation in high-risk populations.

Discrete placental gene expression signatures accompany diabetic disease classifications during pregnancy

Gestational diabetes mellitus (GDM) affects up to 10% of pregnancies and is classified into subtypes GDMA1 (managed by lifestyle modifications) and GDMA2 (requiring medication). However, whether these subtypes are distinct clinical entities or more reflective of an extended spectrum of normal pregnancy endocrine physiology remains unclear. Integrated bulk RNA-sequencing (RNA-seq), single-cell RNA-sequencing (scRNA-seq), and spatial transcriptomics harbors the potential to reveal disease gene signatures in subsets of cells and tissue microenvironments. We aimed to combine these high-resolution technologies with rigorous classification of diabetes subtypes in pregnancy. We hypothesized that differences between pre-existing Type 2 and gestational diabetes subtypes would be associated with altered gene expression profiles in specific placental cell populations. In a large case-cohort design, we compared validated cases of GDMA1, GDMA2, and type 2 diabetes (T2DM) to healthy controls by bulk RNA-seq (n=54). Quantitative analyses with RT-qPCR of presumptive genes of significant interest were undertaken in an independent and non-overlapping validation cohort of similarly well-characterized cases and controls (n=122). Additional integrated analyses of term placental single-cell, single-nuclei, and spatial transcriptomics data enabled us to determine the cellular subpopulations and niches that aligned with the GDMA1, GDMA2, and T2DM gene expression signatures at higher resolution and with greater confidence. Dimensional reduction of the bulk RNA-seq data revealed that the most common source of placental gene expression variation was the diabetic disease subtype. Relative to controls, we found 2,052 unique and significantly differentially expressed genes (-2<Log2(fold-change)>2 thresholds; q<0.05 Wald Test) among GDMA1 placental specimens, 267 among GDMA2, and 1,520 among T2DM. Several candidate marker genes (CSH1, PER1, PIK3CB, FOXO1, EGFR, IL2RB, SOD3, DOCK5, and SOGA1) were validated in an independent and non-overlapping validation cohort (q<0.05 Tukey). Functional enrichment revealed the pathways and genes most impacted for each diabetes subtype, and the degree of proximal similarity to other subclassifications. Surprisingly, GDMA1 and T2DM placental signatures were more alike by virtue of increased expression of chromatin remodeling and epigenetic regulation genes, while albumin was the top marker for GDMA2 with increased expression of placental genes in the wound healing pathway. Assessment of these gene signatures in single-cell, single-nuclei, and spatial transcriptomics data revealed high specificity and variability by placental cell and microarchitecture types. For example, at the cellular and spatial (e.g., microarchitectural) levels, distinguishing features were observed in extravillous trophoblasts (GDMA1) and macrophages (GDMA2). Lastly, we utilized these data to train and evaluate four machine learning models to estimate our confidence in predicting the control or diabetes status of placental transcriptome specimens with no available clinical metadata. Consistent with the distinct association of perinatal outcome risk, placentae from GDMA1, GDMA2, and T2DM-affected pregnancies harbor unique gene signatures that can be further distinguished by altered placental cellular subtypes and microarchitectural niches.

The Influence of Gold, Black Gold, and Digital Gold on Stock Market Portfolios

This research paper aims to study the influence of Bitcoin (BTC), Crude Palm Oil (CPO), Crude Oil (WTI), the Dollar Rate (USD), and Gold (XAU), on Stock Market Portfolios (KLSE). Time series data for this investigation was obtained from Yahoo Finance and Investing.com. Furthermore, the Unit Root Test conducted found that the variables are stationary after 1st differencing. Moreover, since there was no Cointegration discovered between the variables, VAR was performed to determine the long-run causality effect, while the Wald Test was conducted to examine the short-run causality effect. The findings revealed that none of the variables contained a long-run relationship, whereas Bitcoin (BTC), Crude Palm Oil (CPO), and Gold (XAU) contained a short-run relationship with the independent variable (KLSE).

Transition towards natural resource rents and green technology to achieve China's COP26 success: A novel insights in the case of trade openness and environmental pollution

This study aimed to investigate the impact of various factors such as natural resource rents, trade openness, green technology innovation, oil prices, and economic growth on environmental pollution in China by covering the period from 1970 to 2021, aligning with the COP26 agenda. These factors included. To accomplish this, we utilized an advanced Quantile Autoregressive Distributed Lag model to scrutinize the short- and long-term quantile patterns for both the dependent and independent variables. The findings reveal that green technologies and natural resource rents play a negative role in reducing emissions, whereas economic growth and trade openness have positive effects on emissions levels in China in the short and long run during different quantile patterns. Additionally, we employed the Wald test to confirm the presence of asymmetric patterns in environmental pollution concerning economic growth, natural resource rents, green technological innovation, and trade openness in both the short and long terms. These results emphasize the significance of prioritizing key policy measures to align with the COP26 agenda, including enhancing green technology via natural resource rents and addressing immediate climate change challenges in China.

RNA-Seq Analysis of Blastocoel Fluid-Conditioned Media From Euploid Embryos Reveals Higher Expression of Specific Mitochondrial Genes in Media From Embryos Associated With Positive Implantation Outcomes [ID 2683525

INTRODUCTION: This retrospective study measured gene expression using RNA-seq of blastocoel fluid-conditioned media from euploid embryos with known implantation status to identify genes associated with implantation outcomes. METHODS: Blastocoel fluid-conditioned media was obtained after biopsy (ploidy status via NextGen sequencing) of intracytoplasmic sperm injection-generated day 5 blastocysts. Media used for RNA-seq were from 10 euploid blastocysts with known implantation outcomes. RNA was extracted, libraries were prepared, NextSeq500 sequencing was performed, and then sequences were aligned to the human genome. After quality control, the total gene count was 15,284. DESeq2 was used to test for differential gene expression. Raw read counts were normalized and variance stabilizing transformations were applied across samples. Log fold change shrinkage methods were used for gene visualization and rankings. Wald test statistic was used to compare implantation outcomes. Adjusted false-discovery rate P value of &lt;.05 was considered statistically significant for differential expressed genes. RESULTS: Several genes were identified in this analysis revealing differential expression when comparing implantation outcomes. Of interest were two mitochondrial genes (DNAJC19 and MT-TK) and the NOA1 (required for mitochondrial function) with higher expression in media from embryos resulting in successful implantation. CONCLUSION: This study implicates mitochondrial function as a key player during preimplantation development that may affect implantation outcomes. DNAJC19 acts to bring proteins into the mitochondrial matrix, MT-TK encodes a mitochondrial tRNA, and NOA1 is a GTP binding protein residing in the mitochondria. The media samples in this study were collected from euploid blastocysts; therefore, gene expression differences detected represent potential molecular markers for predicting implantation success.

AN ANALYSIS OF THE LONG-TERM ASYMMETRIC RELATIONSHIP BETWEEN GOLD PRICES, EXCHANGE RATES, YIELDS OF GOVERNMENT BOND, AND THE BIST100 INDEX

This study examines the asymmetric effects of the gold price, the USD/TRY exchange rate, the corporate governance index, and the 10-year government bond yield on the BIST100 index, thus delving into the intricate web of financial markets. Using weekly data from September 2007 to September 2023, we employed the nonlinear ARDL model to examine the asymmetric effects of the variables on the BIST100 index. As a result, the nonlinear ARDL bound test proved the long-term cointegration between the BIST100 index and the explanatory variables used in the analysis. All asymmetric variables except the negative variable of gold price had statistically significant long-run effects on the BIST100 index. Government bond yields and gold price had negative effects on the stock index, while USD/TRY exchange rate and corporate governance index had positive effects on it. The Wald test's null hypothesis of no long-term asymmetries was rejected for government bond yields, the USD/TRY exchange rate, and the corporate governance index. On the other hand, the test for short-term asymmetry was rejected only for the corporate governance index. Accordingly, the corporate governance index has both short-term and long-term asymmetric effects on the BIST100 index, while government bond yields and the dollar exchange rate have only long-term asymmetric effects on it.

Impact of Information and Communication Technologies on Energy Consumption and Economic Growth: An Empirical Assessment for China

Regarding the association between information and communication technology (ICT) and economic growth and energy consumption, particularly in developing economies, there is a great deal of controversy and a lack of empirical study. This study applies Quantile Autoregressive Distributed Lag Model (QARDL) approach to empirically probe into the effect of ICT on energy consumption and economic growth in China. Two corresponding models for energy consumption and economic growth are formulated and the data of all of the variables spanning over 1995-2021 period is taken from different secondary sources. The findings of the study reveal significant and positive impact of ICT on economic growth at all quantiles in the short and long run. Similarly ICT has significant and positive impact on energy consumption also at all quantiles. The Quantile Granger Causality test provides evidence for bidirectional causality between ICT and economic growth and ICT and energy consumption. Wald test proved the presence of and symmetric and linear association between ICT and economic growth and ICT and energy consumption at quantiles in the long and short run both. In the light of these findings, the study recommends the Chinese government and investors to have more investment in energy efficient ICT products that consume less energy and help increase in economic growth in China.