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Inferring Multidimensional Rates of Aging from Cross-Sectional Data [article]

Emma Pierson, Pang Wei Koh, Tatsunori Hashimoto, Daphne Koller, Jure Leskovec, Nicholas Eriksson, Percy Liang
2019 arXiv   pre-print
Motivated by the study of human aging, we present an interpretable latent-variable model that learns temporal dynamics from cross-sectional data.  ...  On the UK Biobank human health dataset, our model reconstructs the observed data while learning interpretable rates of aging associated with diseases, mortality, and aging risk factors.  ...  However, most of its data is cross-sectional: 95% of its participants are measured at a single time point. Can we learn how individuals change over time purely from such cross-sectional data?  ... 
arXiv:1807.04709v3 fatcat:jobkallrnzejnd2j32twp4qlau

Monetary and Multidimensional Child Poverty: A Contradiction in Terms?

Keetie Roelen
2017 Development and Change  
data and primary qualitative data from adults and children.  ...  data and primary qualitative data from adults and children.  ...  Sample sizes per cross-sectional wave and for the full panel data are presented in Table 1 .  ... 
doi:10.1111/dech.12306 fatcat:jw4mx3ajhnf2dhzpgovjm4nvnm

Individual differences in human brain development

Timothy T. Brown
2016 Wiley Interdisciplinary Reviews: Cognitive Science  
across age as a result of development.  ...  A recent multidimensional modeling study is explained, which was able to use brain measures to predict an individual's chronological age within about one year on average, in children, adolescents, and  ...  This work was supported by funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R24HD075489), the National Science Foundation (SMA1041755), and the National  ... 
doi:10.1002/wcs.1389 pmid:27906499 pmcid:PMC5682852 fatcat:rlfwu3hjvvegbn5rswcqiovaei

Multidimensional Mathematical Demography: An Overview [chapter]

Kenneth C. Land, Andrei Rogers
1982 Multidimensional Mathematical Demography  
the final chapter of this section, focuses primarily on the problem of estimating transition probabilities from the latter type of data.  ...  In the large majority of cases, however, multidimensional data are simply not available at the level of detail required and must be inferred from available sources by such means as multiproportional adjustment  ... 
doi:10.1016/b978-0-12-435640-5.50007-9 fatcat:bcqui3ef6bau3dokfbxmlyq4fm

Was Pro-Poor Economic Growth in Australia for the Income-Poor? And for the Multidimensionally-Poor?

Francisco Azpitarte
2013 Social Indicators Research  
The sensitivity of pro-poor growth evaluations to the de...nition of poverty is evaluated by comparing the results for the standard income-poverty measure with those based on a multidimensional de...nition  ...  In addition, our results indicate that growth was clearly more pro-income poor than pro-multidimensionally poor.  ...  Estimates derived using cross-sectional enumerated person weights.Source: Author's calculation using HILDA data.  ... 
doi:10.1007/s11205-013-0378-8 fatcat:u5yakibi2bcu5h2f7oiytf7yqu

Systematic review on the association between employee worktime control and work–non-work balance, health and well-being, and job-related outcomes

Hylco H Nijp, Debby GJ Beckers, Sabine AE Geurts, Philip Tucker, Michiel AJ Kompier
2012 Scandinavian Journal of Work, Environment and Health  
Limited to moderately strong cross-sectional evidence was found for positive associations between multidimensional WTC and our outcome categories.  ...  We distinguished between cross-sectional, longitudinal, and intervention studies. Evidence strength was assessed based on the number of studies and their convergence in terms of study findings.  ...  Four of these (39, 47, 64, 78) reported both cross-sectional and longitudinal data and, for these studies, we will consider both cross-sectional and longitudinal associations.  ... 
doi:10.5271/sjweh.3307 pmid:22678492 fatcat:mu7uws3o4zfa3cxg7yoczcsdgq

Methods and Data Sources for Measuring Socio-Economic Factors: A Literature Review

Yasmina Vizuete-Salazar, Marco Segura-Morales
2018 Zenodo  
This article compiles a series of alternative data sources and methods that can be applied to reduce the costs and the time required to update such information.  ...  The compiling of the population data, to establish its socioeconomic factors, is a high-cost task for governments and regulatory organizations due to the need for financial and human resources.  ...  The section VII presents the conclusions of the research. Finally, new opportunities of research, derived from this review, are offered. II.  ... 
doi:10.5281/zenodo.5703518 fatcat:3unbpfwetretbdkxtfp3ycuyzi

Cross-national study of the structure and level of multidimensional self-concepts: An application of confirmatory factor analysis

Herbert W. Marsh, Ian D. Smith
1987 Australian journal of psychology  
The purposes of the present investigation are to compare the structure and level of multidimensional self-concepts for boys and girls from England and Australia, and to demonstrate the use of confirmatory  ...  The results of the study provide further evidence of the generality of multidimensional self-concepts as inferred by the Self Description Questionnaire, rnd demonstrate recent advances in the application  ...  Few cross-national or cross-cultural investigations of multidimensic :ial self-concepts have been conducted, but there are a variety of reasons why the structure and level of self-concept inferred from  ... 
doi:10.1080/00049538708259036 fatcat:jtolyi4t4zfnfnk56ksbmevhsy

Machine learning approach for multidimensional poverty estimation

Mario Esteban Ochoa Guaraca, Ricardo Castro, Alexander Arias Pallaroso, Antonia Machado, Dolores Sucozhañay
2021 Revista Tecnológica - ESPOL  
An error of 7.5% was obtained in the cross-validation and 7.48% with the test data set.  ...  The objective is to estimate the multidimensional poverty index at the personal level in a particular territory of Ecuador by using Machine Learning (ML) regression models based on a limited amount of  ...  Acknowledgments This work is the result of the research project entitled "Unreported crime figure: Links between multidimensional poverty and the human right of access to justice", funded by the Research  ... 
doi:10.37815/rte.v33n2.853 fatcat:hyq4m4a64zanhkz2tcn4337j6u

Age-specific profiles of tissue-level composition and mechanical properties in murine cortical bone

Mekhala Raghavan, Nadder D. Sahar, David H. Kohn, Michael D. Morris
2012 Bone  
specimens of different age-classes.  ...  A retrospective data mining approach was implemented using non-linear multidimensional visualization and classification to identify spectroscopic and nanoindentation metrics that best discriminated bone  ...  R90-DK071506 (Sahar) and a University of Michigan Barbour scholarship (Raghavan).  ... 
doi:10.1016/j.bone.2011.12.026 pmid:22285889 pmcid:PMC3299845 fatcat:awxl6327j5dshamphqtfg7tz5y

Risk factors for dysmenorrhea among Ghanaian undergraduate students

Ayokunle Osonuga, Martins Ekor
2019 African Health Sciences  
The study was a descriptive cross-sectional study involving to two hundred female undergraduate students of the University of Cape Coast (UCC), Ghana.  ...  Menstrual pain is one of the common gynaecological presentations of women of reproductive age to health care physicians.  ...  Methodology Data collection The study was descriptive cross-sectional study involving two hundred female undergraduate students drawn from various faculties of the University of Cape Coast, Ghana.  ... 
doi:10.4314/ahs.v19i4.20 pmid:32127874 pmcid:PMC7040311 fatcat:ys4tikoasbchrfjfcz74suvhui

Associations between community well-being and hospitalisation rates: results from a cross-sectional study within six US states

Brita Roy, Carley Riley, Jeph Herrin, Erica Spatz, Brent Hamar, Kenneth P Kell, Elizabeth Y Rula, Harlan Krumholz
2019 BMJ Open  
ObjectiveTo evaluate the association between community well-being, a positively framed, multidimensional assessment of the health and quality of life of a geographic community, and hospitalisation rates.DesignCross-sectional  ...  In our final model, adjusted for WBI respondent age, sex, race/ethnicity and income, and zip code number of hospital beds, primary care physician density, hospital density and admission rates for two low-variation  ...  Acknowledgements We would like to acknowledge the generous support of Ashlin Jones and Larissa Loufman in the design of this study and preparation of the manuscript.  ... 
doi:10.1136/bmjopen-2019-030017 pmid:31780588 pmcid:PMC6886944 fatcat:jvk5imk43fav3jpgnc4lrdppcq


2020 Psychologia  
We spontaneously infer the social traits of people from their appearance.  ...  The current study demonstrated that two axes provided by multidimensional scaling analysis to the dissimilarity data could be interpreted in terms of valence and power dimensions.  ...  S.I. contributed to acquisition of data. S.I. analyzed the data. S.I. and S.S. contributed in interpreting the results. S.I. and S.S. wrote the paper.  ... 
doi:10.2117/psysoc.2019-a114 fatcat:im4a2x6kfrbhtliyedhtnbuveu

Bayesian Analysis of Multidimensional Functional Data [article]

John Shamshoian, Damla Senturk, Shafali Jeste, Donatello Telesca
2019 arXiv   pre-print
In this paper we focus on longitudinal functional data, a structured form of multidimensional functional data.  ...  Statistical inference is based on Monte Carlo samples from the posterior measure through adaptive blocked Gibbs sampling.  ...  In hierarchical and multidimensional functional data settings, starting from the seminal work of Morris and others (2003) , and recent extensions in Lee and others (2019) , the prevalent strategy has  ... 
arXiv:1909.08763v1 fatcat:l73gdqeswrbhxamlryqolwu4rm

Models of the aging brain structure and individual decline

Gabriel Ziegler
2012 Frontiers in Neuroinformatics  
The presented models first address the estimation of age trajectories, then we consider inter-individual variations of structural decline, using a repeated measures design.  ...  Together these methods afford analysis of aging brain structure in relation to behavioral, health, or cognitive parameters.  ...  annual decline rates obtained from either longitudinal or cross-sectional studies.  ... 
doi:10.3389/fninf.2012.00003 pmid:22435060 pmcid:PMC3303090 fatcat:hdxpbkadbvc43lbghh646fjmum
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