Bayesian Analysis in Regression Models Using Pseudo-Likelihoods

This article deals with the issue of using a suitable pseudo-likelihood, instead of an integrated likelihood, when performing Bayesian inference about a scalar parameter of interest in the presence of nuisance parameters. The proposed approach has the advantages of avoiding the elicitation on the nuisance parameters and the computation of multidimensional integrals. Moreover, it is particularly useful when it is difficult, or even impractical, to write the full likelihood function.

We focus on Bayesian inference about a scalar regression coefficient in various regression models. First, in the context of non-normal regression-scale models, we give a theroetical result showing that there is no loss of information about the parameter of interest when using a posterior distribution derived from a pseudo-likelihood instead of the correct posterior distribution. Second, we present non trivial applications with high-dimensional, or even infinite-dimensional, nuisance parameters in the context of nonlinear normal heteroscedastic regression models, and of models for binary outcomes and count data, accounting also for possibile overdispersion. In all these situtations, we show that non Bayesian methods for eliminating nuisance parameters can be usefully incorporated into a one-parameter Bayesian analysis.     

Maximum likelihood estimation of variance components in a completely random bib design

ABSTRACT

The purposes of this paper are to abstract from a number of articles variance component estimation procedures which can be used for completely random balanced incomplete block designs, to develop an iterated least squares (ITLS) computing algorithm for calculating maximum likelihood estimates, and to compare these procedures by use of simulated experiments. Based on the simulated experiments, the estimated mean square errors of the ITLS estimates are generally less than*those for previously proposed analysis of variance and symmetric sums estimators.     

The questions of fit in the gregor mendel controversy

Ever since R. A. Fisher published his 1936 article , "Has Mendel's Work Been Rediscovered?", historians of both biclogy and statistics have been fascinated by the surprisingly high conformity between Gregor (Johann) Mendel's observed and expected ratios in his famous experiments with peas. Fisher's calculatftl x² statistic of the experiments, taken as a whole, suggested that results on a par or better than those Mendel reported coultl only be expected to occur about three times in every 100,000 attempts. The ensuing controversy as to whether or not the good Father "sophisticated" his data has continued to this very day. In recent years the controversy has focused upon the more technical question of what underlying genetic arrangement Mendel actually studied.

The statistical issues of the controversy are exam:.led in am historical and comparative perspective. The changes the controversy has gone through are evaluated, and the nature of its current, more biological, status is briefly discussed.     

Indigenous data,indigenous methodologies and indigenous data sovereignty

The field of Indigenous methodologies has grown strongly since Tuhiwai Smith’s 1999 groundbreaking book Decolonizing Indigenous Methodologies. For the most part however, there has been a marked absence of quantitative methodologies with the methods aligned with Indigenous methodologies predominantly qualitative. This article proposes that the absence of an Indigenous presence from Indigenous data production has resulted in an overwhelming statistical narrative of deficit for dispossessed Indigenous peoples around the globe. Using the theoretical concept of Indigenous Lifeworlds this article builds on the core premises of Walter and Andersen’s 2013 book Indigenous quantitative methodologies. Arguing for a fundamental disturbance of the Western logics of statistical data the article details recent developments in the field including the emergence of the Indigenous Data Sovereignty movement. The article also explores Indigenous quantitative methodologies in practice using the case study of a Tribal Epidemiology Centre in New Mexico.     

How Have Other Journals Compared to “The Top Seven” Journals in Family Social Science with Respect to LGBT-Related Research and Reviews? A Comment on “A Content Analysis of LGBT Research in Top Family Journals 2000–2015”? An Editorial Analysis

Van Eeden-Moorefield, Few-Demo, Benson, Bible, and Lummer (2018) recently reviewed the content of seven family social science journals with respect to theory and methods used in 153 articles featuring LGBT research or reviews of LGBT research. They concluded that less than three percent of 6,832 articles published in those journals between 2000 and 2015 were LGBT-related and that most had not used explicit theory and had used purposive cross-sectional samples consisting mostly of White and middle-class participants. During the tenure of the present editor, between 2010 and 2017, Marriage & Family Review featured 14 research reports, reviews, or commentary on LGBT-related issues out of 250 articles, not counting brief editorials or biographies between 2010 and 2017, an odds ratio of over 2.0 compared to the other “top-tier” journals. Likewise, the Journal of Family Theory & Review published at least 15 articles, mainly reviews or commentaries, on LGBT-related issues between 2009 and 2017. Articles in Marriage & Family Review and Journal of Family Theory & Review were more likely to be reviews of the literature, or feature explicit theory, to be qualitative in methodology, or to involve interviews or surveys, while other characteristics were similar to those in the other seven journals. Thus, even if some mainstream family journals did not publish often on LGBT-related issues, other important family science journals have done so. Furthermore, there are numerous scholarly journals that welcome LGBT-related research and reviews almost exclusively.     

Evidence-based practice: a critical reflection

This article employs the process of critical reflection to uncover and challenge the hegemonic assumptions of evidence-based practice (EBP). The critical reflection process results in a re-conceptualisation of best practices that, while still honouring empirical research, is less hierarchical and more inclusive of a broad spectrum of interests than traditional EBP. Multidimensional Evidence-Based Practice (MEBP) validates consumer wisdom, professional experience, and qualitative research as equal partners to quantitative research in determining current state-of-the art best practices. Furthermore, MEBP incorporates a value-critical analysis of those best practices that can lead to improvements and innovations, so that ‘best practices’ becomes a dynamic rather than a static construct.     

The FARSEEING real-world fall repository: a large-scale collaborative database to collect and share sensor signals from real-world falls

Background

Real-world fall events objectively measured by body-worn sensors can improve the understanding of fall events in older people. However, these events are rare and hence challenging to capture. Therefore, the FARSEEING (FAll Repository for the design of Smart and sElf-adaptive Environments prolonging Independent livinG) consortium and associated partners started to build up a meta-database of real-world falls.

Results

Between January 2012 and December 2015 more than 300 real-world fall events have been recorded. This is currently the largest collection of real-world fall data recorded with inertial sensors. A signal processing and fall verification procedure has been developed and applied to the data. Since the end of 2015, 208 verified real-world fall events are available for analyses. The fall events have been recorded within several studies, with different methods, and in different populations. All sensor signals include at least accelerometer measurements and 58 % additionally include gyroscope and magnetometer measurements. The collection of data is ongoing and open to further partners contributing with fall signals. The FARSEEING consortium also aims to share the collected real-world falls data with other researchers on request.

Conclusions

The FARSEEING meta-database will help to improve the understanding of falls and enable new approaches in fall risk assessment, fall prevention, and fall detection in both aging and disease.