Cargando…

Meta-analysis of diagnostic accuracy studies in mental health

OBJECTIVES: To explain methods for data synthesis of evidence from diagnostic test accuracy (DTA) studies, and to illustrate different types of analyses that may be performed in a DTA systematic review. METHODS: We described properties of meta-analytic methods for quantitative synthesis of evidence....

Descripción completa

Detalles Bibliográficos
Autores principales:	Takwoingi, Yemisi, Riley, Richard D, Deeks, Jonathan J
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BMJ Publishing Group 2015
Materias:	Statistics in Practice
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4680179/ https://www.ncbi.nlm.nih.gov/pubmed/26446042 http://dx.doi.org/10.1136/eb-2015-102228

Ejemplares similares

Performance of methods for meta-analysis of diagnostic test accuracy with few studies or sparse data
por: Takwoingi, Yemisi, et al.
Publicado: (2015)

Cochrane diagnostic test accuracy reviews
por: Leeflang, Mariska MG, et al.
Publicado: (2013)

Tool to assess risk of bias in studies estimating the prevalence of mental health disorders (RoB-PrevMH)
por: Tonia, Thomy, et al.
Publicado: (2023)

Meta-analysis of test accuracy studies: an exploratory method for investigating the impact of missing thresholds
por: Riley, Richard D, et al.
Publicado: (2015)

Methods and reporting of systematic reviews of comparative accuracy were deficient: a methodological survey and proposed guidance
por: Takwoingi, Yemisi, et al.
Publicado: (2020)

Vitruvian plot: a visualisation tool for multiple outcomes in network meta-analysis
por: Ostinelli, Edoardo Giuseppe, et al.
Publicado: (2022)

Study designs: Part 8 - Meta-analysis (I)
por: Ranganathan, Priya, et al.
Publicado: (2020)

Study designs: Part 9 – Meta-analysis (II)
por: Ranganathan, Priya, et al.
Publicado: (2021)

Diagnostic accuracy of screening tests for COPD: a systematic review and meta-analysis
por: Haroon, Shamil, et al.
Publicado: (2015)

metaumbrella: the first comprehensive suite to perform data analysis in umbrella reviews with stratification of the evidence
por: Gosling, Corentin J, et al.
Publicado: (2023)

Common pitfalls in statistical analysis: Understanding the properties of diagnostic tests – Part 1
por: Ranganathan, Priya, et al.
Publicado: (2018)

Improving the prediction accuracy of river inflow using two data pre-processing techniques coupled with data-driven model
por: Nazir, Hafiza Mamona, et al.
Publicado: (2019)

Understanding the properties of diagnostic tests – Part 2: Likelihood ratios
por: Ranganathan, Priya, et al.
Publicado: (2018)

Use of the experience sampling method in the context of clinical trials
por: Verhagen, Simone J W, et al.
Publicado: (2016)

Understanding diagnostic tests – Part 3: Receiver operating characteristic curves
por: Aggarwal, Rakesh, et al.
Publicado: (2018)

Predicting outcomes at the individual patient level: what is the best method?
por: Liu, Qiang, et al.
Publicado: (2023)

Eustachian tube dysfunction: A diagnostic accuracy study and proposed diagnostic pathway
por: Smith, Matthew E., et al.
Publicado: (2018)

Common pitfalls in statistical analysis: Linear regression analysis
por: Aggarwal, Rakesh, et al.
Publicado: (2017)

Common pitfalls in statistical analysis: Intention-to-treat versus per-protocol analysis
por: Ranganathan, Priya, et al.
Publicado: (2016)

Accuracy of single progesterone test to predict early pregnancy outcome in women with pain or bleeding: meta-analysis of cohort studies
por: Verhaegen, Jorine, et al.
Publicado: (2012)

Common pitfalls in statistical analysis: Measures of agreement
por: Ranganathan, Priya, et al.
Publicado: (2017)

Common pitfalls in statistical analysis: Logistic regression
por: Ranganathan, Priya, et al.
Publicado: (2017)

Common pitfalls in statistical analysis: Odds versus risk
por: Ranganathan, Priya, et al.
Publicado: (2015)

Common pitfalls in statistical analysis: The perils of multiple testing
por: Ranganathan, Priya, et al.
Publicado: (2016)

Common pitfalls in statistical analysis: The use of correlation techniques
por: Aggarwal, Rakesh, et al.
Publicado: (2016)

Study designs: Part 2 – Descriptive studies
por: Aggarwal, Rakesh, et al.
Publicado: (2019)

Study designs: Part 4 – Interventional studies
por: Aggarwal, Rakesh, et al.
Publicado: (2019)

Study designs: Part 3 - Analytical observational studies
por: Ranganathan, Priya, et al.
Publicado: (2019)

Study designs: Part 5 – Interventional studies (III)
por: Ranganathan, Priya, et al.
Publicado: (2020)

Study designs: Part 5 – interventional studies (II)
por: Aggarwal, Rakesh, et al.
Publicado: (2019)

Common pitfalls in statistical analysis: Clinical versus statistical significance
por: Ranganathan, Priya, et al.
Publicado: (2015)

Survival analysis in clinical trials: Basics and must know areas
por: Singh, Ritesh, et al.
Publicado: (2011)

Common pitfalls in statistical analysis: “No evidence of effect” versus “evidence of no effect”
por: Ranganathan, Priya, et al.
Publicado: (2015)

Common pitfalls in statistical analysis: “P” values, statistical significance and confidence intervals
por: Ranganathan, Priya, et al.
Publicado: (2015)

Research studies on screening tests
por: Aggarwal, Rakesh, et al.
Publicado: (2022)

Declining Accuracy in Disease Classification on Health Insurance Claims: Should We Reconsider Classification by Principal Diagnosis?
por: Okamoto, Etsuji
Publicado: (2010)

Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat
por: Ranganathan, Priya, et al.
Publicado: (2016)

Study designs: Part 1 – An overview and classification
por: Ranganathan, Priya, et al.
Publicado: (2018)

Study designs: Part 7 – Systematic reviews
por: Ranganathan, Priya, et al.
Publicado: (2020)

Dependence structure analysis of multisite river inflow data using vine copula-CEEMDAN based hybrid model
por: Nazir, Hafiza Mamona, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_hkfbr5ca0iam3fr74vk2kj4e0g