17 papers · ranked by Valyu relevance
Dan Jackson, Richard Riley, Ian R White
The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and…
Matthew Stephens, Frank Emmert-Streib
We consider the problem of assessing associations between multiple related outcome variables, and a single explanatory variable of interest. This problem arises in many settings, including genetic association studies, where the explanatory variable is genotype at a genetic variant. We outline a framework for conducting…
Dan Jackson, Ian R White, Richard D Riley
Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I2 statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to…
Troy Vargason, Daniel P. Howsmon, Deborah L. McGuinness, Juergen Hahn
'Juergen Hahn'] Data analysis used for biomedical research, particularly analysis involving metabolic or signaling pathways, is often based upon univariate statistical analysis. One common approach is to compute means and standard deviations individually for each variable or to determine where each variable falls…
Glaucia Cristina Rodrigues Nascimento, Marcela Baraúna Magno, Giseon Heo, David Normando
High-dimensional data hinder sample visualization and limit exploration of data1. In these cases, we can make use of multivariate analysis techniques, such as Factor Analysis (FA) and/or Principal Component Analysis (PCA), to reduce a complex data set to one of lower dimensions so as to reveal any hidden features and…
Eric Houngla Adjakossa, Ibrahim Sadissou, Mahouton Norbert Hounkonnou, Gregory Nuel + 1 more
'Gregory Nuel' 'Lourens J Waldorp'] In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more…
Daniel Krähmer, Cristobal Young, Nate Breznau
Multiverse analysis is an increasingly popular tool for improving the robustness and transparency of empirical research. Yet, visualization techniques for multiverse analysis are underdeveloped. We identify critical weaknesses in existing multiverse visualizations-specification curves and density plots-and introduce a…
Patrício Soares Costa, Nadine Correia Santos, Pedro Cunha, Jorge Cotter + 1 more
'Jorge Cotter' 'Nuno Sousa'] The main focus of this study was to illustrate the applicability of multiple correspondence analysis (MCA) in detecting and representing underlying structures in large datasets used to investigate cognitive ageing. Principal component analysis (PCA) was used to obtain main cognitive…
Dan Jackson, Ian R White, Richard D Riley
Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of…
Uwe Thissen, Suzan Wopereis, Sjoerd AA van den Berg, Ivana Bobeldijk + 5 more
'Robert Kleemann' 'Teake Kooistra' 'Ko Willems van Dijk' 'Ben van Ommen' 'Age K Smilde'] Background In the fields of life sciences, so-called designed studies are used for studying complex biological systems. The data derived from these studies comply with a study design aimed at generating relevant information while…
Daniel Jackson, Richard D Riley
Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing…
Mark de Rooij, Ligaya Breemer, Dion Woestenburg, Frank Busing
We present a multidimensional data analysis framework for the analysis of ordinal response variables. Underlying the ordinal variables, we assume a continuous latent variable, leading to cumulative logit models. The framework includes unsupervised methods, when no predictor variables are available, and supervised…
John B. Copas, Dan Jackson, Ian R. White, Richard D. Riley
Title: Summary Univariate meta-analysis concerns a single outcome of interest measured across a number of independent studies. However, many research studies will have also measured secondary outcomes. Multivariate meta-analysis allows us to take these secondary outcomes into account and can also include studies where…
Anita Brobbey, Samuel Wiebe, Alberto Nettel-Aguirre, Colin Bruce Josephson + 3 more
generalized estimation equations Authors: ['Anita Brobbey' 'Samuel Wiebe' 'Alberto Nettel-Aguirre' 'Colin Bruce Josephson' 'Tyler Williamson' 'Lisa M Lix' 'Tolulope T. Sajobi'] Discriminant analysis procedures that assume parsimonious covariance and/or means structures have been proposed for distinguishing between two…
Angélique O. J. Cramer, Don van Ravenzwaaij, Dora Matzke, Helen Steingroever + 4 more
'Helen Steingroever' 'Ruud Wetzels' 'Raoul P. P. P. Grasman' 'Lourens J. Waldorp' 'Eric-Jan Wagenmakers'] Many psychologists do not realize that exploratory use of the popular multiway analysis of variance harbors a multiple-comparison problem. In the case of two factors, three separate null hypotheses are subject to…
Christian Acal, Ana M. Aguilera
The methodological contribution in this paper is motivated by biomechanical studies where data characterizing human movement are waveform curves representing joint measures such as flexion angles, velocity, acceleration, and so on. In many cases the aim consists of detecting differences in gait patterns when several…
Gabriel Romero Liguori, Luiz Felipe Pinho Moreira
III. Comparing Groups Authors: Gabriel Romero Liguori, Luiz Felipe Pinho Moreira When working with three or more groups, like comparing treatments A, B, and C, another type of statistical test must be used, the so-called analysis of variance (ANOVA). Maybe some of the readers are asking themselves why not to perform…