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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1948 2
1950 1
1958 1
1960 2
1962 4
1963 1
1964 2
1965 1
1967 1
1969 1
1975 1
1976 3
1978 3
1979 3
1980 5
1981 4
1982 6
1983 8
1984 12
1985 17
1986 11
1987 14
1988 27
1989 233
1990 818
1991 934
1992 1125
1993 1373
1994 1602
1995 1842
1996 2051
1997 2466
1998 2369
1999 2514
2000 2647
2001 3063
2002 3158
2003 3537
2004 3972
2005 4304
2006 4484
2007 4653
2008 5220
2009 5874
2010 6183
2011 7252
2012 10316
2013 10686
2014 9571
2015 9673
2016 9847
2017 9493
2018 6506
2019 2696
2020 38
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123,654 results
Results by year
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Page 1
A univariate perspective of multivariate genome-wide association analysis.
Guo X, et al. Genet Epidemiol 2018. PMID 29781551
However, fundamental questions remain open, including the conditions and reasons under which the multivariate analysis is beneficial, how a highly significant signal arises in the multivariate analysis. ...A real data analysis is employed to illustrate how to interpret how the signals arising from multivariate GWASs....
However, fundamental questions remain open, including the conditions and reasons under which the multivariate analysis is beneficial, …
[Multivariate analysis].
Mélot C. Rev Mal Respir 2005 - Review. PMID 16294189 French.
Statistical and Multivariate Analysis of MS-Based Plant Metabolomics Data.
Jaeger C and Lisec J. Methods Mol Biol 2018. PMID 29761446
We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming environment R, useful to normalize data, detect biomarkers, and perform sample classification....
We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming envir …
WASP (Write a Scientific Paper): Multivariate analysis.
Grech V and Calleja N. Early Hum Dev 2018. PMID 29680331
Multivariate analysis is a statistical modeling technique wherein multiple x variables are analysed simultaneously for their effect on y, resulting in an additive model (via an equation) that explains the observation/s and corrects for confounding association/s using one dependent and several independent variables, assigning a gradient to each of these independent variables, and with all product terms of gradient and magnitude of the independent variables adding up to estimate 'y'. ...
Multivariate analysis is a statistical modeling technique wherein multiple x variables are analysed simultaneously for their effect o
Exploratory multivariate analysis of hospital admissions data in conjunction with workforce data.
Yang Xie , et al. Conf Proc IEEE Eng Med Biol Soc 2017. PMID 29060438
Exploratory multivariate analysis methods, such as principal component analysis (PCA) and multiple correspondence analysis (MCA), were applied to study important variables associated with admission and workforce data. ...
Exploratory multivariate analysis methods, such as principal component analysis (PCA) and multiple correspondence analysis (MCA), wer …
Multivariate optimization techniques in food analysis - A review.
Ferreira SLC, et al. Food Chem 2019 - Review. PMID 30292370 Free article.
This work presents a critical review of multivariate techniques employed for optimization of methods developed in food analysis. ...
This work presents a critical review of multivariate techniques employed for optimization of methods developed in food analysis. ...
A need for a standardization in anaerobic digestion experiments? Let's get some insight from meta-analysis and multivariate analysis.
Lavergne C, et al. J Environ Manage 2018. PMID 29807264
This study presents a meta-analysis coupled with multivariate analysis aiming to assess the impact of this experimental variability in batch and continuous operation at mesophilic and thermophilic anaerobic digestion of waste activated sludge. ...
This study presents a meta-analysis coupled with multivariate analysis aiming to assess the impact of this experimental variability i …
A guide to statistical analysis in microbial ecology: a community-focused, living review of multivariate data analyses.
Buttigieg PL and Ramette A. FEMS Microbiol Ecol 2014 - Review. PMID 25314312 Free article.
The application of multivariate statistical analyses has become a consistent feature in microbial ecology. However, many microbial ecologists are still in the process of developing a deep understanding of these methods and appreciating their limitations. ...To address these issues, we present the GUide to STatistical Analysis in Microbial Ecology (GUSTA ME): a dynamic, web-based resource providing accessible descriptions of numerous multivariate techniques relevant to microbial ecologists. ...
The application of multivariate statistical analyses has become a consistent feature in microbial ecology. However, many microbial ec …
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