Introduction to Random Effects Meta Analysis

Studies were assessed and data were pooled using random-effects meta-analysis based on the Cochrane handbook.

Two independent investigators extracted study-level data for a random-effects meta-analysis.

We conducted random-effects meta-analysis when appropriate.

We pooled findings across provinces using random-effects meta-analysis.

We performed a random-effects meta-analysis of all outcomes.

Pooled effects were calculated by inverse-variance random-effects meta-analysis.

Mean disability weight estimates, sorted by the grade of leprosy disability as defined by WHO, were estimated for individual participant data and pooled using multivariate random-effects meta-analysis.

We extracted the reported data and we performed random-effects meta-analysis to obtain the summary Odds Ratios (OR) with 95% Confidence Intervals.

Then, we obtained national overall effects by random-effects meta-analysis.

METHOD A systematic review was performed in the Pubmed/MEDLINE, Embase, LILACS, and PsycINFO databases for original studies investigating symptoms of depression and anxiety and diagnoses of major depressive disorder and anxiety disorders in PLWH, and a random-effects meta-analysis with meta-regression was performed to obtain a summary frequency of symptoms and diagnoses of depression and anxiety.

METHODS With simulations mimicking a typical study in UK Biobank, we assessed the performance, in terms of bias and precision of the MR estimate, of the fixed-effect and (multiplicative) random-effects meta-analysis method, weighted median estimator, weighted mode estimator and MR-Egger regression, used in both one-sample and two-sample data.

Random-effects meta-analysis provided a combined effect size and examined which mode of digital interventions had the largest effects on flu vaccination.

RESULTS The random-effects meta-analysis of 7 eligible RCTs demonstrated the significant decline in both SBP (WMD - 5.

Summary estimates were pooled by use of random-effects meta-analysis.

DATA SYNTHESIS Data was pooled using random-effects meta-analysis.

A two-stage IPD meta-analysis framework was applied: (1) Cox proportional hazard models assessed time-to-mortality of participants with radiographic OA (ROA), OA-related pain (POA), and a combination of pain and ROA (PROA) against pain and ROA-free participants; (2) hazard ratios (HR) were then pooled using the Hartung–Knapp modification for random-effects meta-analysis.

64%); random-effects meta-analysis yielded an odds ratio of 2.

Data from the included trials were pooled by using random-effects meta-analysis of the weighted mean difference (MD) between the comparator groups.

A multivariate, random-effects meta-analysis was run using metafor in R.

Pooled proportions were calculated using a random-effects meta-analysis model.

Pooled LTBI prevalence among adults with HBV was calculated using a random-effects meta-analysis model.

The selected studies were put in a pool of results using a random-effects meta-analysis, with standardized mean differences and calculation of 95% confidence intervals.

A random-effects meta-analysis of standardized mean differences (SMD) was performed for several performance variables.

The primary outcome measure was changed in self-reported alcohol consumption analysed by random-effects meta-analysis.

Multivariateadjusted risk ratios (RRs) with 95% confidence interval (CI) for stroke in different level intake of fish or Longchain omega-3 polyunsaturated fatty acids (LC ω3-PUFAs) were pooled using a random-effects meta-analysis.

A random-effects meta-analysis was performed to analyze these data.

A random-effects meta-analysis of 37 independent samples (n = 5795) found a statistically significant association between higher stigma and lower subjective QoL of medium strength (r = -0.

The random-effects meta-analysis model was employed to estimate the pooled proportion of good HTN SCPs.

Random-effects meta-analysis was used to generate pooled treatment effects and 95% confidence intervals.

A frequentist-based approach with a multivariate random-effects meta-analysis was used.

Random-effects meta-analysis models were used to estimate the odds ratios (OR), and heterogeneity associated with the outcomes.

All eligible data were collected using a pre-designed data extraction form, and the overall prevalence was estimated using a random-effects meta-analysis model.

We performed random-effects meta-analysis and carried out subgroup analysis according to type of underlying diseases and type of SGLT2 inhibitors.

Random-effects meta-analysis revealed an overall non-significant difference in creativity scores between those with dyslexia and controls.

Estimates of findings from both studies were pooled in random-effects meta-analysis.

With evidence from 112 field trials and 13,998 study subjects between 1976 and 2021, this study systematically evaluated and compared the energy-saving effects of monetary and nonmonetary interventions using a random-effects meta-analysis approach.

Random-effects meta-analysis found a significantly improved likelihood of prehospital return of spontaneous circulation (pooled odds ratio (OR) = 1.

Lastly, a random-effects meta-analysis model was fitted to estimate the pooled proportion of knowledge, attitude, and prevention practices toward COVID-19 in Ethiopia.

Risk estimates of each relevant outcome were pooled as a hazard ratio (HR) with a 95% confidence interval (CI) using the random-effects meta-analysis model.

Descriptive analyses of all studies were performed and when more than four studies were avail-able, a random-effects meta-analysis was used to estimate pooled sensitivity and specificity in comparison to reverse transcriptase polymerase chain reaction testing.

Effect sizes for continuous outcomes were based on the standardised mean difference (SMD), combined using standard random-effects meta-analysis (all with 95% CIs).

A random-effects meta-analysis estimated combined odds ratios (OR) and 95% confidence intervals (CI), using the most adjusted model from each study.

METHODS We conducted a random-effects meta-analysis of randomised clinical trials assessing PCSK9-targeting therapies, namely alirocumab, evolocumab and inclisiran, in patients with clinically diagnosed HeFH and restricted analyses to those patients in whom genotypic data were available.

Random-effects meta-analysis was conducted to obtain pooled estimates.

Effect estimates were pooled using a DerSimonian and Laird random-effects meta-analysis model.

A logistic-normal random-effects meta-analysis was performed to calculate % positive alternative-specimen, % positive NP, and % dual positives overall and in subgroups.

Random-effects meta-analysis was undertaken where ≥2 studies were sufficiently similar in intervention and outcome.

METHODS AND RESULTS  We performed a random-effects meta-analysis of all RCTs comparing ultrathin-strut DES to conventional 2nd-generation thin-strut DES.

We conducted a random-effects meta-analysis with inverse-probability weighting.

Random-effects meta-analysis was performed for all-cause 5-year (main outcome) and 3-year mortality, and disease-specific 5-year and 3-year mortality.

A random-effects meta-analysis was then used to compare the multivariate risk estimates of the lowest CRF group from each cohort with the group of the highest CRF.

We calculated the pooled overall and regional estimates by random-effects meta-analysis.

All SR and trial-level data were imported into the statistical software and all meta-analyses were replicated using the cumulative random-effects meta-analysis approach.

A random random-effects meta-analysis was utilizedused.

Data were pooled using random-effects meta-analysis.

Overall and subgroup pooled prevalence of GDM was quantified by random-effects meta-analysis.

Risk estimates of each relevant outcome were pooled as a hazard ratio (HR) with a 95% confidence interval (CI) using the random-effects meta-analysis model.

A systematic review and random-effects meta-analysis was also conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) protocol.

Random-effects meta-analysis was used to combine effect estimates and estimate heterogeneity.

Cox regression estimated multivariable-adjusted HRs and 95% confidence intervals (CI) for associations of the age at menarche with risk of each cancer in each cohort and random-effects meta-analysis was used to generate summary estimates for each cancer.

In addition to the narrative synthesis, where sufficient data are available, a random-effects meta-analysis will be conducted to obtain a pooled estimate value for respectful maternity care prevalence and outcomes.

We calculated summary risk estimates across cohorts using pooled analysis and random-effects meta-analysis.

Random-effects meta-analysis was used to combine adjusted estimates across studies.

Where possible, we pooled data using random-effects meta-analysis, by CMA software.

Random-effects meta-analysis suggested no significant effects on the levels of fasting blood glucose [-7.

A random-effects meta-analysis was conducted for post-reperfusion outcomes in AIS patients with absent-to-mild leukoaraiosis and moderate-to-severe leukoaraiosis.

For each local authority, we modelled the weekly change in R (the R ratio) per a rescaled weekly percentage change in each location-specific mobility metric relative to a pre-pandemic baseline period (Jan 3–Feb 6, 2020), with results synthesised across local authorities using a random-effects meta-analysis.

We propose new random-effects meta-analysis methods using five flexible random-effects distribution models that can flexibly regulate skewness, kurtosis and tailweight: skew normal distribution, skew t-distribution, asymmetric Subbotin distribution, Jones-Faddy distribution, and sinh-arcsinh distribution.

Data were pooled using a random-effects meta-analysis.

Methods: After systematically searched associated studies up to 1st December 2020, we performed a fixed and random-effects meta-analysis using the Stata software and evaluated the quality of included studies by the risk of bias scale of the Cochrane collaboration tool.

A random-effects meta-analysis was performed to analyze the pooled incidence and odds ratios of VTE in patients with different driver genes.

The pooled analyses were calculated by random-effects meta-analysis.

METHODS A random-effects meta-analysis was conducted following the PRISMA guidelines.

Incidence, prevalence, and odds ratio of outcomes were extracted and pooled by random-effects meta-analysis.

Random-effects meta-analysis was used to quantify the relative and absolute risk of frailty in women compared with men with HF, overall, and by Physical and Multidimensional Frailty measures.

A random-effects meta-analysis was performed.

We pooled effect sizes using random-effects meta-analysis.

Adjusted cohort-specific effect estimates were combined using random-effects meta-analysis.

A random-effects meta-analysis with restricted maximum likelihood estimation was performed to obtain pooled effect estimates.

We conducted a three-level random-effects meta-analysis on the impact of satirical news ( k = 70, Ntotal = 22,969).

The association of physical activity with survival was evaluated by combining study-specific hazard ratios with random-effects meta-analysis models.

Estimates were pooled using random-effects meta-analysis.

We performed a random-effects meta-analysis of cortisol responses in first-episode psychosis (FEP) and psychosis risk states, taking into consideration glucose metabolism.

A random-effects meta-analysis was implemented that combined ADKS scores from independent studies.