Prediction intervals for all of M future observations based on linear random effects models

Prediction intervals are commonly used in meta-analysis with random-effects models. One widely used method, the Higgins–Thompson–Spiegelhalter prediction interval, replaces the heterogeneity parameter with its point estimate, but its validity strongly depends on a large sample approximation. This is a weakness in meta-analyses with few studies. We propose an alternative based on bootstrap and show by simulations that its coverage is close to the nominal level, unlike the Higgins–Thompson–Spiegelhalter method and its extensions. The proposed method was applied in three meta-analyses.

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Generalized prediction intervals for treatment effects in random‐effects models

Biometrical Journal ◽

10.1002/bimj.201700255 ◽

2018 ◽

Vol 61 (5) ◽

pp. 1242-1257 ◽

Cited By ~ 1

Author(s):

Razaw Al‐Sarraj ◽

Claudia von Brömssen ◽

Johannes Forkman

Keyword(s):

Random Effects ◽

Treatment Effects ◽

Prediction Intervals ◽

Random Effects Models

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Positional Estimation Within a Latent Space Model for Networks

Methodology ◽

10.1027/1614-2241.2.1.24 ◽

2006 ◽

Vol 2 (1) ◽

pp. 24-33 ◽

Cited By ~ 17

Author(s):

Susan Shortreed ◽

Mark S. Handcock ◽

Peter Hoff

Keyword(s):

Random Effects ◽

Network Data ◽

Random Effects Models ◽

Space Model ◽

Network Analyses ◽

Recent Advances ◽

Latent Space ◽

Latent Space Model ◽

Modeling Data

Recent advances in latent space and related random effects models hold much promise for representing network data. The inherent dependency between ties in a network makes modeling data of this type difficult. In this article we consider a recently developed latent space model that is particularly appropriate for the visualization of networks. We suggest a new estimator of the latent positions and perform two network analyses, comparing four alternative estimators. We demonstrate a method of checking the validity of the positional estimates. These estimators are implemented via a package in the freeware statistical language R. The package allows researchers to efficiently fit the latent space model to data and to visualize the results.

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Dyslipidaemia and mortality in COVID-19 patients - a meta-analysis

QJM ◽

10.1093/qjmed/hcab071 ◽

2021 ◽

Author(s):

Marco Zuin ◽

Gianluca Rigatelli ◽

Claudio Bilato ◽

Carlo Cervellati ◽

Giovanni Zuliani ◽

...

Keyword(s):

Random Effects ◽

Mortality Risk ◽

Meta Analysis ◽

Random Effect ◽

Final Analysis ◽

Short Term ◽

Random Effects Models ◽

Pooled Prevalence ◽

Statistical Heterogeneity ◽

Trim And Fill

Abstract Objective The prevalence and prognostic implications of pre-existing dyslipidaemia in patients infected by the SARS-CoV-2 remain unclear. To perform a systematic review and meta-analysis of prevalence and mortality risk in COVID-19 patients with pre-existing dyslipidaemia. Methods Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed in abstracting data and assessing validity. We searched MEDLINE and Scopus to locate all the articles published up to January 31, 2021, reporting data on dyslipidaemia among COVID-19 survivors and non-survivors. The pooled prevalence of dyslipidaemia was calculated using a random effects model and presenting the related 95% confidence interval (CI), while the mortality risk was estimated using the Mantel-Haenszel random effects models with odds ratio (OR) and related 95% CI. Statistical heterogeneity was measured using the Higgins I2 statistic. Results Eighteen studies, enrolling 74.132 COVID-19 patients [mean age 70.6 years], met the inclusion criteria and were included in the final analysis. The pooled prevalence of dyslipidaemia was 17.5% of cases (95% CI: 12.3-24.3%, p < 0.0001), with high heterogeneity (I2=98.7%). Pre-existing dyslipidaemia was significantly associated with higher risk of short-term death (OR: 1.69, 95% CI: 1.19-2.41, p = 0.003), with high heterogeneity (I2=88.7%). Due to publication bias, according to the Trim-and-Fill method, the corrected random-effect ORs resulted 1.61, 95% CI 1.13-2.28, p < 0.0001 (one studies trimmed). Conclusions Dyslipidaemia represents a major comorbidity in about 18% of COVID-19 patients but it is associated with a 60% increase of short-term mortality risk.

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Association of bisphenol A with puberty timing: a meta-analysis

Reviews on Environmental Health ◽

10.1515/reveh-2020-0091 ◽

2020 ◽

Vol 0 (0) ◽

Author(s):

Hui Meng ◽

Yunping Zhou ◽

Yunxia Jiang

Keyword(s):

Bisphenol A ◽

Confidence Intervals ◽

Random Effects ◽

Strong Correlation ◽

Fixed Effects ◽

Meta Analysis ◽

Random Effects Models ◽

Study Heterogeneity ◽

The Relationship ◽

Prevalence Ratios

AbstractObjectivesThe results of existing studies on bisphenol A (BPA) and puberty timing did not reach a consensus. Thereby we performed this meta-analytic study to explore the association between BPA exposure in urine and puberty timing.MethodsMeta-analysis of the pooled odds ratios (OR), prevalence ratios (PR) or hazards ratios (HR) with 95% confidence intervals (CI) were calculated and estimated using fixed-effects or random-effects models based on between-study heterogeneity.ResultsA total of 10 studies involving 5621 subjects were finally included. The meta-analysis showed that BPA exposure was weakly associated with thelarche (PR: 0.96, 95% CI: 0.93–0.99), while no association was found between BPA exposure and menarche (HR: 0.99, 95% CI: 0.89–1.12; OR: 1.02, 95% CI: 0.73–1.43), and pubarche (OR: 1.00, 95% CI: 0.79–1.26; PR: 1.00, 95% CI: 0.95–1.05).ConclusionsThere was no strong correlation between BPA exposure and puberty timing. Further studies with large sample sizes are needed to verify the relationship between BPA and puberty timing.

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Random effects models of lymph node metastases in breast cancer: quantifying the roles of covariates and screening using a continuous growth model

Biometrics ◽

10.1111/biom.13430 ◽

2021 ◽

Author(s):

Gabriel Isheden ◽

Kamila Czene ◽

Keith Humphreys

Keyword(s):

Breast Cancer ◽

Lymph Node ◽

Random Effects ◽

Growth Model ◽

Lymph Node Metastases ◽

Continuous Growth ◽

Random Effects Models ◽

Node Metastases

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EXPRESS: A meta-analysis of aspirin and subarachnoid haemorrhage in patients with intracranial aneurysms yields different results to the general population

International Journal of Stroke ◽

10.1177/17474930211004888 ◽

2021 ◽

pp. 174749302110048

Author(s):

Frederick Ewbank ◽

Jacqueline Birks ◽

Diederik Bulters

Keyword(s):

General Population ◽

Subarachnoid Haemorrhage ◽

Confidence Intervals ◽

Random Effects ◽

Intracranial Aneurysms ◽

Meta Analysis ◽

Risk Of Bias ◽

Random Effects Models ◽

Hazard Ratios ◽

Unruptured Intracranial Aneurysms

Abstract Background Some studies have shown a protective association between aspirin use and subarachnoid haemorrhage (SAH). Other studies have found no relationship or the reverse. These studies differ in their study populations and definitions of SAH. Aims Our aim was to establish 1) if there is an association between aspirin and SAH, 2) how this differs between the general population and those with intracranial aneurysms. Summary of review Studies reporting aspirin use and the occurrence of SAH were included and grouped based on population (general population vs aneurysm population). Odds ratios, hazard ratios and confidence intervals were combined in random-effects models. 11 studies were included. Overall, there was an association between aspirin and SAH (OR 0.68 [0.48, 0.96]). However, populations were diverse and heterogeneity between studies high (p<0.00001), questioning the validity of combining these studies and justifying analysis by population. In the general population there was no difference in aspirin use between individuals with and without SAH (OR 1.15 [0.96, 1.38]). In patients with intracranial aneurysms, aspirin use was greater in patients without SAH (OR 0.37 [0.24, 0.58]), although these studies were at higher risk of bias. Conclusions There is an association between aspirin use and SAH in patients with intracranial aneurysms. This apparent protective relationship is not seen in the general population. Prospective randomised studies are required to further investigate the effect of aspirin on unruptured intracranial aneurysms.

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