scholarly journals Meta-analysis of SNP-environment interaction with heterogeneity for overlapping data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qinqin Jin ◽  
Gang Shi
Keyword(s):  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Type I ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Overlapping Data ◽  
Effect Model

AbstractMeta-analysis is a popular method used in genome-wide association studies, by which the results of multiple studies are combined to identify associations. This process generates heterogeneity. Recently, we proposed a random effect model meta-regression method (MR) to study the effect of single nucleotide polymorphism (SNP)-environment interactions. This method takes heterogeneity into account and produces high power. We also proposed a fixed effect model overlapping MR in which the overlapping data is taken into account. In the present study, a random effect model overlapping MR that simultaneously considers heterogeneity and overlapping data is proposed. This method is based on the random effect model MR and the fixed effect model overlapping MR. A new way of solving the logarithm of the determinant of covariance matrices in likelihood functions is also provided. Tests for the likelihood ratio statistic of the SNP-environment interaction effect and the SNP and SNP-environment joint effects are given. In our simulations, null distributions and type I error rates were proposed to verify the suitability of our method, and powers were applied to evaluate the superiority of our method. Our findings indicate that this method is effective in cases of overlapping data with a high heterogeneity.

scholarly journals Relation Between Cigarette Smoking and Sarcopenia: Meta-Analysis

2015 ◽  
pp. 419-426 ◽  
Author(s):  
M. STEFFL ◽  
R. W. BOHANNON ◽  
M. PETR ◽  
E. KOHLIKOVA ◽  
I. HOLMEROVA
Keyword(s):  
Risk Factor ◽  
Cigarette Smoking ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Effect Model ◽  
The Individual ◽  
The Relationship

Cigarette smoking is a risk factor for many diseases. It could be associated with sarcopenia. The aim of this meta-analysis was to determine whether smoking is an isolated risk factor for sarcopenia. We searched PubMed, Web of Science, EBSCO, and Science Direct for articles addressing the relationship between cigarette smoking and sarcopenia. A total of 12 studies containing information on 22,515 participants were included in this meta-analysis. Odds ratio (OR) was calculated for each study group and for all studies together. An OR was also calculated separately for each sex. We used a fixed-effect model in overall estimation and in males, because results of small studies were significantly different from the results of large studies in those cases and in females where the estimation showed only moderate heterogeneity we used a random-effect model. According to proposes of the Cochrane Handbook for Systematic Reviews. The resulting OR in the fixed-effect model was 1.12 (95 % CI 1.03-1.21), OR for each sex was in the fixed-effect model 1.20 (95 % CI 1.06-1.35) in males and in the random-effect model 1.21 (95 % CI 0.92-1.59) in females. The results of this meta-analysis indicate that cigarette smoking as an isolated factor may contribute to the development of sarcopenia. However, the results of the individual studies were largely inconsistent due to different approaches of measuring the main variables which affected the results.

scholarly journals Comparative efficacy between ketamine, memantine, riluzole and d-cycloserine in patients diagnosed with drug resistant depression: a meta-analysis

2019 ◽  
Vol 8 (6) ◽  
pp. 1132
Author(s):  
Nishita H. Darji ◽  
Devang A. Rana ◽  
Supriya D. Malhotra
Keyword(s):  
Rating Scale ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect ◽  
P Value ◽  
Drug Resistant ◽  
Effect Model ◽  
Resistant Depression ◽  
Glutamate Modulators

Background: Glutamate modulators are having immense potential and are newer entities for treating drug resistant depression. The objectives were to generate statistical evidence on basis of existing data of ketamine, memantine, riluzole and d-cycloserine in resistant depression.Methods: A total of 14 RCTs following PRISMA guidelines and matching inclusion and exclusion criteria were collected of ketamine (5), memantine (3), riluzole (2) and d-cycloserine (4) vs placebo in drug resistant depression. Only RCTs with primary diagnosis of drug resistant depression (Previously on two standard antidepressant therapy) were included. Studies with treatment response rate, 50% reduction in total score of the depression rating scale-Montgomery-Åsberg Depression Rating Scale or the Hamilton Depression Rating Scale or Beck Depression Inventory was chosen as clinical outcome measure. RevMan 5.3 software was used for the analysis.Results: In ketamine group using random effect model SMD was 2.122 (95% CI 0.659-3.584). P-value was statistically significant (random effect p <0.005 and in fixed effect <0.001). In memantine group, using random effect model -0.963 was SMD and (95% CI -1.958-0.0324). P-value was <0.001, significant in fixed effect. In riluzole group, SMD was -0.564 with (95% CI -3.927-2.799) in random effect. P-value was 0.741. In d-cycloserine group SMD was 0.316 with (95% CI -1.252-1.885) in random effect. P-value was 0.690.Conclusions: Ketamine showed best efficacy followed by memantine. Riluzole and DCS as such have no efficacy although its acts by same glutamate pathway. More molecular based research is required in use of glutamate modulators in resistant depression.

scholarly journals The Correlation of Glycemic Index, Glycemic Load, and Carbohydrates with the Risk of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

2021 ◽  
Author(s):  
Long-Shan Yang ◽  
Guang-Xiao Meng ◽  
Zi-Niu Ding ◽  
Lun-Jie Yan ◽  
Sheng-Yu Yao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Glycemic Index ◽  
Hepatitis Virus ◽  
Meta Analysis ◽  
Glycemic Load ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Case Control Studies ◽  
Effect Model

Abstract Background Glycemic index (GI), glycemic load (GL), and carbohydrates have been shown to be associated with a variety of cancers, but their correlation with hepatocellular carcinoma (HCC) remains controversial. The purpose of our study was to investigate the correlation of GI, GL and carbohydrate with risk of HCC.Methods Systematic searches were conducted in PubMed, Embase and Web of Science until November 2020. According to the size of heterogeneity, the random effect model or the fixed effect model was performed to calculate the pooled relative risks (RRs) and 95% confidence intervals (CIs) for the correlation of GI, GL, and carbohydrates with the risk of HCC.Results Seven cohort studies involving 1,193,523 participants and 1,004 cases, and 3 case-control studies involving 827 cases and 5,502 controls were eventually included. The pooled results showed no significant correlation of GI (RR=1.11, 95%CI 0.80-1.53, I2= 62.2%), GL (RR=1.09, 95%CI 0.76-1.55, I2 = 66%), and carbohydrate (RR=1.09, 95%CI 0.84-1.32, I2=0%) with the risk of HCC in general population. Subgroup analysis revealed that in hepatitis B virus (HBV) or/and hepatitis C virus (HCV)-positive group, GI was not correlated with the risk of HCC (RR=0.65, 95%CI 0.32-1.32, p=0.475, I2=0.0%), while GL was significantly correlated with the risk of HCC (RR=1.52, 95%CI 1.04-2.23, p=0.016, I2=70.9%). In contrast, in HBV and HCV-negative group, both GI (RR=1.23, 95%CI 0.88-1.70, p=0.222, I2=33.6%) and GL (RR=1.17, 95% CI 0.83-1.64, p=0.648, I2=0%) were not correlated with the risk of HCC. Conclusion A high GL diet is correlated with a higher risk of HCC in people with hepatitis virus. A low GL diet may be recommended for patients with viral hepatitis to reduce the risk of HCC.

Effect of Dividend on Stock Price: A Case of Fuel and Power Industries in Bangladesh

2019 ◽  
Vol 9 (2) ◽  
pp. 87
Author(s):  
Mir Md Nazrul Islam
Keyword(s):  
Stock Price ◽  
Dividend Policy ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Return On Equity ◽  
Share Prices ◽  
Earnings Per Share ◽  
Effect Model

Dividend policy is an extensively researched topic in the arena of investments but still it remains an enigmatic that whether Dividend Policy affects the Stock Prices or not. The consequences of researches conducted in different stock markets are different. In Bangladesh, capital market investment is very essential and significant for the growth and market capitalization of domestic industry, trade and commerce. In current years Bangladesh had faced many precarious situations in its stock market. The Stock price reactions to the declaration of dividend of the fuel and power industry of Bangladesh are empirically examined. This study examines stock price reactions of listed dividend paying fuel and power industries in Dhaka stock exchange, Bangladesh for period of 11 years from of 2008-2018. This study will help us to make effective dividend decisions and effective implementation of dividend policies. In this study, Fixed Effect Model along with Random Effect Model have been used to estimate results. Both Models are implemented on panel data for explaining the association between dividend payments and share prices while controlling logarithm value of Profit after Tax, Earnings per Share and Return on Equity. The research is accompanied with a view to find whether the dividend announcement convey any evidence to the market that results a stock price volatility for adjusting the dividend announcement information while controlling the variables like Profit After Tax Earnings, Per Share and Return on Equity. The study also tested both the Models and found Random Effect Model is more significant than Fixed Effect Model. The result documented on the Random Effect Model shows that there are significant relationship with Retention Ratio, dividend per share and Return on Equity. In addition, Profit after tax shows the negative significant association and Earning per Shares insignificant with the share prices in Bangladesh Fuel and Power sector. 

scholarly journals Cyp2C19*2 Polymorphism Related to Clopidogrel Resistance in Patients With Coronary Heart Disease, Especially in the Asian Population: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 11 ◽  
Author(s):  
Ying Sun ◽  
Qing Lu ◽  
Xuefei Tao ◽  
Biao Cheng ◽  
Guoxing Yang
Keyword(s):  
Gene Polymorphism ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Asian Population ◽  
Fixed Effect Model ◽  
Clopidogrel Resistance ◽  
Effect Model ◽  
The Relationship ◽  
Allele Model

In recent years, the relationship between Cyp2C19*2 gene polymorphism and clopidogrel resistance reflected by platelet function assay has been studied extensively, but there is no clear conclusion yet. In order to evaluate the relationship between Cyp2C19*2 gene polymorphism and clopidogrel resistance more accurately, meta-analysis was conducted in this study. The I2 value taking 50% as the limit, the heterogeneity is judged as high or low, and then a random effect model or a fixed effect model is selected for statistical analysis. PubMed, EMBASE, Web of Science, CNKI, and China Wanfang database were searched, and the related literatures from the establishment of the database to May 2020 were collected and analyzed by STATA 15.0 software. A total of 3,073 patients were involved in 12 studies, including 1,174 patients with clopidogrel resistance and 1,899 patients with non-clopidogrel resistance. The results of this study showed that allele model (A vs. G): OR = 2.42 (95%CI: 1.97–2.98); dominant model (AA+GA vs. GG): OR = 2.74 (95%CI: 2.09–3.59); recessive model (AA vs. GA+GG): OR = 4.07 (95%CI: 3.06–5.41); homozygous model (AA vs. GG): OR = 5.70 (95%CI: 4.22–7.71); heterozygote model (GA vs. GG): OR = 2.32 (95%CI: 1.76–3.07), the differences were statistically significant. Also, the analysis of the Ethnicity subgroup indicated that the Asian allele model and the other four gene models were statistically significant. In conclusion, Cyp2C19*2 gene polymorphism is strongly associated with clopidogrel resistance. Allele A, genotype GA, AA, and GG + GA can increase clopidogrel resistance, especially in the Asian population.

scholarly journals Is MGNREG Scheme Complementary to Fishing Activities?

2016 ◽  
Vol 5 (1) ◽  
pp. 47-53
Author(s):  
Chiranjib Neogi ◽  
Kamal Ray ◽  
Ramesh Chandra Das
Keyword(s):  
Freshwater Fish ◽  
Rainwater Harvesting ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Series Data ◽  
Component Part ◽  
Indian States ◽  
Effect Model

Freshwater fish output is taken as a proxy variable for empirical assessment of indirect benefits in terms of enhanced quantity of freshwater fish (output) cultivation. It is not unlikely to assess empirically the productivity of subsidized public scheme when rural development or rural asset generations are underlined in the said scheme, MGNREG Act, 2005. Rainwater harvesting is a major component part of the scheme since about 49.5 per cent of the total fund is already utilized on water conservation and obviously it has an impact on the cultivation of freshwater fish output. Time series data on annual expenditure on MGNREG and corresponding freshwater fish output at the state level are taken during the period 2006-07 to 2013-14 for 16 major Indian states. Fixed effect model and random effect models are being applied and the Hausman specification test suggests that fixed effect model is more appropriate than random effect model. Significant differences among the intercepts of the selected states are revealed as per F test. The results of fixed effect panel regression establish that fish output is enhanced by 0.000257 thousand tones or 0.26 tones if MGNREG expenditure rises by one crore or 10 million rupees. 

scholarly journals History and Spread of Viruses (COVID-19) and Associated Demographic and Clinical Parameters – A systematic review and meta-analysis

2021 ◽  
Vol 33 (1) ◽  
pp. 9-24
Author(s):  
Swambhavi Awasthi ◽  
Sunil Sharma ◽  
Saurav Attri ◽  
Sakshi Malik Attri ◽  
Rajesh Sharawat ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Primary Objective ◽  
Asymptomatic Patients ◽  
Effect Model ◽  
Co Morbidity ◽  
The Common ◽  
Meta Analyses

COVID-19 made a huge impact on the world due to its rapid transmission and no treatments being available for it. The virus affected more people and spread to various countries than what was predicted when COVID-19 initially began spreading. There have been numerous pandemics and epidemics in the 21st century yet COVID-19 has affected more people and spread widely. The primary objective of the study was to explore history, spread and associated parameters of existing viruses especially COVID-19. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was followed for a systematic search to identify eligible published articles. Clinical data, regarding COVID-19 patients, was obtained from previously published articles. The main cause of COVID-19 spreading rapidly was noted to be due to a high percentage of asymptomatic patients, transmission being air-borne, and the lack of knowledge and preventative measures being implemented when the virus began spreading. The common co-morbidity that found in patients was Diabetes Mellitus, Hypertension, and Coronary Heart Disease. The common symptoms, found through the Meta-analysis, that the patients faced included cough (55.4%), fever (68.4%), fatigue (20.3%), and shortness of breath (18.1%). The proportion of asymptotic positive cases was measured 58.3% (95%CI: 24.7% – 87.9%) while mortality proportion was found to be 6.7% (fixed-effect model) and 13.4% (random-effect model). The Meta-analysis indicated that a higher percentage of males were affected by COVID-19 than females and more patients are found to be asymptomatic. Moreover, the mortality rate of patients that have had COVID-19 was found to be low. 

scholarly journals A Bayesian Model-Averaged Meta-Analysis of the Power Pose Effect with Informed and Default Priors: The Case of Felt Power

2017 ◽  
Author(s):  
Quentin Frederik Gronau ◽  
Sara van Erp ◽  
Daniel W. Heck ◽  
Joseph Cesario ◽  
Kai Jonas ◽  
...  
Keyword(s):  
Bayesian Model ◽  
Bayesian Model Averaging ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Model Averaging ◽  
Fixed Effect Model ◽  
Body Postures ◽  
Effect Model ◽  
Meta Analyses

Carney, Cuddy, and Yap (2010) found that --compared to participants who adopted constrictive body postures-- participants who adopted expansive body postures reported feeling more powerful, showed an increase in testosterone and a decrease in cortisol, and displayed anincreased tolerance for risk. However, these power pose effects have recently come under considerable scrutiny. Here we present a Bayesian meta-analysis of six preregistered studies from this special issue, focusing on the effect of power posing on felt power. Our analysisimproves on standard classical meta-analyses in several ways. First and foremost, we considered only preregistered studies, eliminating concerns about publication bias. Second, the Bayesian approach enables us to quantify evidence for both the alternative and the null hypothesis. Third, we use Bayesian model-averaging to account for the uncertainty with respect to the choice for a fixed-effect model or a random-effect model. Fourth, based on a literature review we obtained an empirically informed prior distribution for the between-studyheterogeneity of effect sizes. This empirically informed prior can serve as a default choice not only for the investigation of the power pose effect, but for effects in the field of psychology more generally. For effect size, we considered a default and an informed prior. Our meta-analysis yields very strong evidence for an effect of power posing on felt power. However, when the analysis is restricted to participants unfamiliar with the effect, the meta-analysis yields evidence that is only moderate.

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