scholarly journals A Primer on Network Meta-Analysis for Dental Research

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Yu-Kang Tu ◽  
Clovis Mariano Faggion
Keyword(s):  
Statistical Approach ◽  
Meta Analysis ◽  
Statistical Methodology ◽  
Close Collaboration ◽  
Dental Research ◽  
Modelling Framework ◽  
Statistical Framework ◽  
General Statistical ◽  
Multiple Treatments ◽  
Further Development

In the last decade, a new statistical methodology, namely, network meta-analysis, has been developed to address limitations in traditional pairwise meta-analysis. Network meta-analysis incorporates all available evidence into a general statistical framework for comparisons of all available treatments. A further development in the network meta-analysis is to use a Bayesian statistical approach, which provides a more flexible modelling framework to take into account heterogeneity in the evidence and complexity in the data structure. The aim of this paper is therefore to provide a nontechnical introduction to network meta-analysis for dental research community and raise the awareness of it. An example was used to demonstrate how to conduct a network meta-analysis and the differences between it and traditional meta-analysis. The statistical theory behind network meta-analysis is nevertheless complex, so we strongly encourage close collaboration between dental researchers and experienced statisticians when planning and conducting a network meta-analysis. The use of more sophisticated statistical approaches such as network meta-analysis will improve the efficiency in comparing the effectiveness between multiple treatments across a set of trials.

scholarly journals Analyzing Stress as a Multivariate Phenotype

2020 ◽  
Vol 60 (1) ◽  
pp. 70-78
Author(s):  
Rory S Telemeco ◽  
Eric J Gangloff
Keyword(s):  
Statistical Approach ◽  
Single Point ◽  
The Novel ◽  
Multivariate Statistical ◽  
Theoretical Understanding ◽  
Online Appendix ◽  
Statistical Framework ◽  
Multiple Biomarkers ◽  
General Statistical ◽  
Multivariate Theory

Abstract The stress phenotype is multivariate. Recent advances have broadened our understanding beyond characterizing the stress response in a single dimension. Simultaneously, the toolbox available to ecophysiologists has expanded greatly in recent years, allowing the measurement of multiple biomarkers from an individual at a single point in time. Yet these advances—in our conceptual understanding and available methodologies—have not yet been combined in a unifying multivariate statistical framework. Here, we offer a brief review of the multivariate stress phenotype and describe a general statistical approach for analysis using nonparametric multivariate analysis of variance with residual randomization in permutation procedures (RRPP) implemented using the “RRPP” package in R. We also provide an example illustrating the novel insights that can be gained from a holistic multivariate approach to stress and provide a tutorial for how we analyzed these data, including annotated R code and a guide to interpretation of outputs (Online Appendix 1). We hope that this statistical methodology will provide a quantitative framework facilitating the unification of our theoretical understanding and empirical observations into a quantitative, multivariate theory of stress.

scholarly journals Current hurdles to the translation of nanomedicines from bench to the clinic

2021 ◽  
Author(s):  
Snežana Đorđević ◽  
María Medel Gonzalez ◽  
Inmaculada Conejos-Sánchez ◽  
Barbara Carreira ◽  
Sabina Pozzi ◽  
...  
Keyword(s):  
Drug Product ◽  
Early Stage ◽  
Regulatory Agencies ◽  
Important Process ◽  
Close Collaboration ◽  
Critical Quality Attributes ◽  
Research Areas ◽  
Physical Chemical ◽  
Clinical Models ◽  
Further Development

AbstractThe field of nanomedicine has significantly influenced research areas such as drug delivery, diagnostics, theranostics, and regenerative medicine; however, the further development of this field will face significant challenges at the regulatory level if related guidance remains unclear and unconsolidated. This review describes those features and pathways crucial to the clinical translation of nanomedicine and highlights considerations for early-stage product development. These include identifying those critical quality attributes of the drug product essential for activity and safety, appropriate analytical methods (physical, chemical, biological) for characterization, important process parameters, and adequate pre-clinical models. Additional concerns include the evaluation of batch-to-batch consistency and considerations regarding scaling up that will ensure a successful reproducible manufacturing process. Furthermore, we advise close collaboration with regulatory agencies from the early stages of development to assure an aligned position to accelerate the development of future nanomedicines. Graphical abstract

Putting relative complexity estimates to work: a simple and general statistical methodology

2003 ◽  
Vol 319 ◽  
pp. 591-600 ◽  
Author(s):  
Lluis nindexLligonaLligoña Trulla ◽  
Joseph P. Zbilut ◽  
Alessandro Giuliani
Keyword(s):  
Statistical Methodology ◽  
Relative Complexity ◽  
General Statistical

scholarly journals Methodological review to develop a list of bias items used to assess reviews incorporating network meta-analysis: protocol and rationale

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e045987
Author(s):  
Carole Lunny ◽  
Andrea C Tricco ◽  
Areti-Angeliki Veroniki ◽  
Sofia Dias ◽  
Brian Hutton ◽  
...  
Keyword(s):  
Systematic Reviews ◽  
Methodological Quality ◽  
Meta Analysis ◽  
Healthcare Providers ◽  
Cochrane Library ◽  
Methodological Review ◽  
Multiple Treatment ◽  
Full Study ◽  
Multiple Treatments ◽  
Treatment Comparisons

IntroductionSystematic reviews with network meta-analysis (NMA; ie, multiple treatment comparisons, indirect comparisons) have gained popularity and grown in number due to their ability to provide comparative effectiveness of multiple treatments for the same condition. The methodological review aims to develop a list of items relating to biases in reviews with NMA. Such a list will inform a new tool to assess the risk of bias in NMAs, and potentially other reporting or quality checklists for NMAs which are being updated.Methods and analysisWe will include articles that present items related to bias, reporting or methodological quality, articles assessing the methodological quality of reviews with NMA, or papers presenting methods for NMAs. We will search Ovid MEDLINE, the Cochrane library and difficult to locate/unpublished literature. Once all items have been extracted, we will combine conceptually similar items, classifying them as referring to bias or to other aspects of quality (eg, reporting). When relevant, reporting items will be reworded into items related to bias in NMA review conclusions, and then reworded as signalling questions.Ethics and disseminationNo ethics approval was required. We plan to publish the full study open access in a peer-reviewed journal, and disseminate the findings via social media (Twitter, Facebook and author affiliated websites). Patients, healthcare providers and policy-makers need the highest quality evidence to make decisions about which treatments should be used in healthcare practice. Being able to critically appraise the findings of systematic reviews that include NMA is central to informed decision-making in patient care.

scholarly journals How Replicates Can Inform Potential Users of a Measurement Procedure about Measurement Error: Basic Concepts and Methods

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 162
Author(s):  
Werner Vach ◽  
Oke Gerke
Keyword(s):  
Measurement Error ◽  
Measurement Procedure ◽  
Statistical Methodology ◽  
Single Measurement ◽  
Conceptual Approach ◽  
Simple Manner ◽  
Scientific Investigations ◽  
Standard Procedures ◽  
Standardized Terminology ◽  
General Statistical

Measurement procedures are not error-free. Potential users of a measurement procedure need to know the expected magnitude of the measurement error in order to justify its use, in particular in health care settings. Gold standard procedures providing exact measurements for comparisons are often lacking. Consequently, scientific investigations of the measurement error are often based on using replicates. However, a standardized terminology (and partially also methodology) for such investigations is lacking. In this paper, we explain the basic conceptual approach of such investigations with minimal reference to existing terminology and describe the link to the existing general statistical methodology. This way, some of the key measures used in such investigations can be explained in a simple manner and some light can be shed on existing terminology. We encourage clearly conceptually distinguishing between investigations of the measurement error of a single measurement procedure and the comparison between different measurement procedures or observers. We also identify an unused potential for more advanced statistical analyses in scientific investigations of the measurement error.

A Statistical Approach to Ranking Similarities of Three Function Structure Groups Using Directed Graphs

2018 ◽  
Author(s):  
Briana M. Lucero ◽  
Matthew J. Adams
Keyword(s):  
Statistical Approach ◽  
Directed Graphs ◽  
Proof Of Concept ◽  
Function Structure ◽  
Fundamental Properties ◽  
Design Engineers ◽  
Functional Representation ◽  
Structure Databases ◽  
Further Development ◽  
Function Structures

Prior efforts in the study of engineering design employed various approaches to decompose product design. Design engineers use functional representation, and more precisely function structures, to define a product’s functionality. However, significant barriers remain to objectively quantifying the similarity between two function structures, even for the same product when developed by multiple designers. For function-structure databases this means that function-structures are implicitly categorized leaving the possibility of incorrect categorization and reducing efficacy of returned analogous correlations. Improvements to efficacy in database organization and queries are possible by objectively quantifying the similarity between function structures. The proposed method exploits fundamental properties of function-structures and design taxonomies. We convert function-structures into directed graphs (digraphs) and equivalent adjacency matrices. The conversion maintains the directed (function → flow → function) progression inherent to function-structures and enables the transformation of the function-structure into a standardized graph. For design taxonomies (e.g. D-APPS), graph nodes represent flows in a consistent (but arbitrary) ordering. By exploiting the directional properties of function-structures and defining the flows as the graphical nodes, the objective and standardized comparison of two function-structures becomes feasible. We statistically quantify the association between digraphs using the Pearson Product Moment Correlation (PPMC) for both within-group and between-group comparisons. The method was tested on three product types (ball thrower, food processor, and an ice cream maker) with function-structures defined by various designers. The method suggested herein is provided as a proof-of-concept with suggested verification and validation approaches for further development.

Comparative efficacy and acceptability of antimanic drugs in acute mania: a multiple-treatments meta-analysis

The Lancet ◽  
2011 ◽  
Vol 378 (9799) ◽  
pp. 1306-1315 ◽  
Author(s):  
Andrea Cipriani ◽  
Corrado Barbui ◽  
Georgia Salanti ◽  
Jennifer Rendell ◽  
Rachel Brown ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Acute Mania ◽  
Comparative Efficacy ◽  
Multiple Treatments

scholarly journals Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models

2017 ◽  
Vol 27 (10) ◽  
pp. 2885-2905 ◽  
Author(s):  
Richard D Riley ◽  
Joie Ensor ◽  
Dan Jackson ◽  
Danielle L Burke
Keyword(s):  
Meta Analysis ◽  
Information Matrix ◽  
Indirect Evidence ◽  
Parameter Estimates ◽  
Individual Participant Data ◽  
One Stage ◽  
Individual Participant ◽  
Meta Regression ◽  
Multiple Treatments ◽  
Analysis Models

Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher’s information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis).

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