# Introduction to Meta Regression Analyses

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## Meta Regression Analyses sentence examples within random effects model

## Meta Regression Analyses sentence examples within subgroup meta regression

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Then, subgroup and meta-regression analyses were conducted to disclose the influence of geographic area, fracture type, administration route, frequency and dosage of TXA, blood transfusion threshold, and follow-up duration on the overall effect.

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Univariate meta-regression analyses found that sham response was associated with higher risk of blinding bias, and with treatment effect size in the active tDCS group.

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Sensitivity and meta-regression analyses were performed.

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Meta-regression analyses partially accounted for the source of heterogeneity, and yet, 53% of the symptoms remained unexplained.

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Additional meta-regression analyses indicated that participant age and clinical status (i.

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The meta-analysis and meta-regression analyses were fit using a random effects model.

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To explore heterogeneity across the studies, univariable and multivariable meta-regression analyses were performed.

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Meta-regression analyses, publication
bias assessment and Trim and Fill function were also performed.

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In meta-regression analyses, the treatment response was associated with patient age (estimated slope, -1.

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Sub-group, sensitivity and meta-regression analyses were performed where data permitted.

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On the other hand, meta-regression analyses performed on gender, age, duration of disease, percentage of patients with ANA+ or RF+, medium value of ESR or CRP were not statistically significant.

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After duplicate study selection, data extraction, and risk-of-bias assessment, random effects meta-analyses of mean differences (MDs) and their 95% confidence intervals (CIs) were performed, followed by subgroup/meta-regression analyses.

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The pooled sensitivity, specificity, and summary area under the receiver operating characteristic curve (AUC) were calculated and meta-regression analyses were performed.

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The meta-regression analyses did not indicate the dose effects of PCs on SBP, DBP, PP and MAP.

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We performed subgroup, sensitivity, and meta-regression analyses.

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Subgroup and meta-regression analyses were conducted for demographic and clinical variables as appropriate.

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Conducting meta-regression analyses, however, we found the relationship between ELM and resting vagal activity to significantly vary as a function of both age and presence of psychopathology.

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Meta-regression analyses did not show a significant influence of RT nor HT on the DFI at 10 years.

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A growing number of meta-analyses supported the application of digital psychotherapeutic intervention across different populations, but relatively few meta- and meta-regression analyses have concentrated on perinatal women.

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Sensitivity analyses will be performed as well as a priori subgroup, meta-regression and multiple meta-regression analyses.

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Pooled mean differences were calculated using a random-effects model, followed by sensitivity and meta-regression analyses.

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In subgroup meta-regression analyses, males with definite fertility had continuous declines in SC (slope northern group=-2.

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A meta-regression analyses determined that intralesional-GTR improved PFS (PHR 0.

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Following the meta-analysis of random effects, the meta-regression analyses were used to explore factors potentially influencing treatment efficacy.

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Meta-regression analyses showed a better hypoglycaemia detection in studies indicating a higher overall accuracy, whereas year of publication did not significantly influence diagnostic accuracy.

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Network meta-analysis was performed to determine the effects of coffee and/or tea consumption on reducing BC risk in a dose-dependent manner and differences in coffee/tea type, menopause status, hormone receptor and the BMI in subgroup and meta-regression analyses.

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Data were analyzed using random-effects modeling, and subgroup and meta-regression analyses were used to ascertain heterogeneity among the subgroups.

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Meta-regression analyses also showed significant differences in lesion-level prevalence with respect to age (p = 0.

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The relationship between each biomarker and WMH burden will be meta-analyzed if possible, with subgroup or meta-regression analyses to assess differences between diseases.

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Data were synthesised with random-effects meta-analyses and meta-regression analyses, applying Grades of Recommendation, Assessment, Development and Evaluation criteria.

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Subgroup analyses were crude univariable meta-regression analyses.

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Temporal trends in clinical outcomes (cardiac death, myocardial infarction [MI], target lesion revascularisation [TLR], stent thrombosis [ST]) were assessed using random-effects meta-regression analyses, estimating the relationship between clinical outcomes and study start year.

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Sources of heterogeneity were not found through subgroup and meta-regression analyses.

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For the moderate response rate, meta-regression analyses revealed that publication year (β = −0.

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Meta-regression analyses were performed to explore heterogeneity.

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Following quality assessment of study eligibility, stratified meta-analysis and meta-regression analyses were undertaken to recognize and control the heterogeneity in meta-analysis.

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To explore sources of heterogeneity, meta-regression analyses were performed.

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The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses.

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We incorporated the effect size using the random-effects model in the “meta” package in R software and conducted univariate and multivariate meta-regression analyses using a mixed-effects model.

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A meta-analysis will be conducted to calculate the pooled effect size of each outcome, and meta-regression analyses will investigate whether intervention features and the presence and absence of individual BCTs in interventions are associated with intervention effectiveness.

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The effects of potential moderators were investigated by both subgroup and meta-regression analyses.

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Our subgroup and meta-regression analyses indicated that prior exposure to ICIs may reduce the incidence of COVID-19 in metastatic cancer patients.

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Given significant heterogeneity across studies, we conducted meta-regression analyses with sample characteristics, age, number of treatment sessions, treatment duration, intervention type, control group type, and study design.

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In subgroup and meta-regression analyses, areas, NOS, mean fluorescence intensity (MFI) cut off, primary diseases, HSCT types, graft sources, and pre-transplant desensitization did not affect the impact of anti-HLA DSAs on primary graft failure (PGF).

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Sources of heterogeneity were explored through subgroup and meta-regression analyses.

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Meta-regression analyses found increasing GM atrophy in the right insula associated with the longer mean abstinence duration of the samples in the studies in our analysis.

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Subgroup and meta-regression analyses were performed to assess for heterogeneity.

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Meta-regression analyses were conducted to estimate regression coefficients.

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Subgroup and meta-regression analyses explored potential sources of heterogeneity in the data.

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Subgroup and random effects meta-regression analyses will be used to further investigate the potential sources of heterogeneity.

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Meta-regression analyses were also performed.

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Subgroup and meta-regression analyses were conducted across covariates, including sampling method and outcome measure.

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In meta-regression analyses of study characteristics, study location (continent) explained some (∼20%) heterogeneity for T1 exposure studies, but no characteristic explained a substantial amount of heterogeneity for T2 exposure studies.

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The meta-regression analyses showed that the glaucoma-progression assessment methods had had a modulating influence (P=.

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Furthermore, the source of heterogeneity was checked by subgroup and meta-regression analyses.

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Meta-regression analyses were performed to assess the influence of patients' age, sex, illness duration, antipsychotic dose, positive and negative symptoms on the study SMDs.

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Meta-regression analyses were performed to explore study heterogeneity.

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Additionally, meta-analysis of variance and meta-regression analyses were performed.

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Meta-regression analyses indicated that greater weight reduction in SGLT2i users was significantly associated with the increased risks of amputation (β = − 0.

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Meta-regression analyses indicated a significant and positive effect of drinks per month on alcohol-induced stimulation (β=.

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We undertook random-effects meta-analyses and meta-regression analyses to calculate the pooled effect and the influence of effect modifiers.

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Sources of heterogeneity will be explored via meta-regression analyses, if possible.

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Meta-regression analyses showed that increasing age and including a higher proportion of people with hypertension was associated with lower retention rates.

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Subgroup and meta-regression analyses were also performed to determine factors influencing heterogeneity affecting the diagnostic performance among the clinical, MRI, and analytic characteristics.

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Meta-regression analyses show a decreasing benefit on HF events with increasing receptor selectivity of SGLT2i.

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Random-effects meta-analyses and meta-regression analyses were performed.

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Leaving-one-out, subgroups and meta-regression analyses showed that study quality and type of BLL testing devices were sources of heterogeneity.

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Subgroup and meta-regression analyses were conducted to explore the associated risk factors and to identify the sources of heterogeneity.

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Meta-regression analyses were performed to assess the relationship between MSC dose and pooled effect sizes in each cell dose.

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We conducted meta-regression analyses on a wide set of dependent measures that control for general slowing, tested for publication bias, and examined four potential methodological moderators.

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The interrelationships between PFS and OS hazard ratios (HRs) and median survival time differences were investigated by conducting fixed-effects and mixed-effects linear meta-regression analyses.

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