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Methods for Mediation Analysis with Missing Data
Psychometrika, 2013Despite wide applications of both mediation models and missing data techniques, formal discussion of mediation analysis with missing data is still rare. We introduce and compare four approaches to dealing with missing data in mediation analysis including listwise deletion, pairwise deletion, multiple imputation (MI), and a two-stage maximum likelihood (
Zhang, Zhiyong, Wang, Lijuan
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2000
BIACORE is a system for real-time analysis of interactions between molecules that can be used for both qualitative and quantitative investigations. In particular, continuous monitoring of both association and dissociation phases in an interaction allows determination of rate and affinity constants.
Tohru Natsume +2 more
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BIACORE is a system for real-time analysis of interactions between molecules that can be used for both qualitative and quantitative investigations. In particular, continuous monitoring of both association and dissociation phases in an interaction allows determination of rate and affinity constants.
Tohru Natsume +2 more
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2019
In this chapter, we give a brief outline of the methods of data analysis used, from elementary T-scores to nonlinear principal component analysis (PCA), including data normalisation, quantification of categorical attributes, categorical principal component analysis (CatPCA), sparse PCA, the method of principal variables, the original ‘double’ Kaiser ...
Elaine Fehrman +5 more
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In this chapter, we give a brief outline of the methods of data analysis used, from elementary T-scores to nonlinear principal component analysis (PCA), including data normalisation, quantification of categorical attributes, categorical principal component analysis (CatPCA), sparse PCA, the method of principal variables, the original ‘double’ Kaiser ...
Elaine Fehrman +5 more
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Streaming Methods in Data Analysis
2015A fundamental challenge in processing the massive quantities of information generated by modern applications is in extracting suitable representations of the data that can be stored, manipulated and interrogated on a single machine. A promising approach is in the design and analysis of compact summaries: data structures which capture key features of ...
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A Data Reconstruction Method for The Big-Data Analysis
2018 9th International Conference on Awareness Science and Technology (iCAST), 2018In recent years, the big-data approach has become important within various business operations and salesjudgment tactics. Contrarily, numerous privacy problems limit the progress of their analysis technologies. To mitigate such problems, this paper proposes several privacy-preserving methods, i.e., anonymization, extreme value record elimination, fully
Masataka Mito +4 more
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2020
In order to evaluate your intervention, you will need to analyse the data that you collected from users of the intervention as well as, where applicable, the comparison group. These data can come either directly via the app or by collecting data through other data sources (e.g. questionnaires).
Alan Davies, Julia Mueller
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In order to evaluate your intervention, you will need to analyse the data that you collected from users of the intervention as well as, where applicable, the comparison group. These data can come either directly via the app or by collecting data through other data sources (e.g. questionnaires).
Alan Davies, Julia Mueller
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A novel method for analysis of TOMROP data
Journal of Magnetic Resonance Imaging, 2004AbstractPurposeTo develop an efficient method for extracting maps of the corrected T1 from images generated using the T One by Multiple Read Out Pulses (TOMROP) sequence.Materials and MethodsAn expression is developed for the true T1 in terms of the parameters from a three‐parameter fit of the TOMROP data. Solutions of gadodiamide in normal saline with
Stephen, Pickup +2 more
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An overview of methods for the analysis of longitudinal data
Statistics in Medicine, 1992AbstractThis paper reviews statistical methods for the analysis of discrete and continuous longitudinal data. The relative merits of longitudinal and cross‐sectional studies are discussed. Three approaches, marginal, transition and random effects models, are presented with emphasis on the distinct interpretations of their coefficients in the discrete ...
S L, Zeger, K Y, Liang
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Methods for phylogenetic analysis of microbiome data
Nature Microbiology, 2018How does knowing the evolutionary history of microorganisms affect our analysis of microbiological datasets? Depending on the research question, the common ancestry of microorganisms can be a source of confounding variation, or a scaffolding used for inference. For example, when performing regression on traits, common ancestry is a source of dependence
Alex D. Washburne +6 more
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Methods and Data for the Analysis
2018In this chapter, we debate the sources of our analysis and the statistical methods used. We also amply discuss the methodological literature on these subjects. Our data sources are the Arab Opinion Index of the Arab Center for Research and Policy Studies in Doha, Qatar; the Arab Barometer, Wave III; the Pew Spring 2015 Survey; the BBC Global Scan; and ...
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