Results 61 to 70 of about 7,315,247 (116)
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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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Analysis of method‐comparison data
Ophthalmic and Physiological Optics, 1994Method‐comparison studies, in which new‘candidate’techniques are compared with an established‘gold standard', feature commonly in optometric research. Investigators often analyse their findings using least squares regression. Pearson's product‐moment correlation coefficient and the paired t‐test.
D E, Shaw, H S, Jones, M J, Moseley
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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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HEART DISEASE DATA ANALYSIS USING EXPLORATORY DATA ANALYSIS METHOD
International Journal of Engineering Applied Sciences and Technology, 2022Health care industry companies generate a large volume of raw data, often called big data, which reveals hidden patterns and knowledge for decision making. Data-driven decisions are more accurate than intuition because they use massive data. In exploratory data analysis, mistakes are detected, data is identified, assumptions are checked, and the ...
Uma K, M Hanumanthappa
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Exploratory Data Analysis Methods
Sociological Methods & Research, 1984This article describes several exploratory data analysis (EDA) methods, which were implemented in a study on work role centrality. The purpose of the study was to find the factors that affect work role centrality of industrial workers. The article illustrates the implementation of EDA methods for revealing relationships among variables, for detecting ...
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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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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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Data Sources and Methods of Data Analysis
2021In recent decades, researchers pragmatically adopted a paradigmatic relativism to overcome the longstanding paradigm of the incompatibility of positivism and constructivism in social science (Morgan 2007, 58; Tashakkori and Teddlie 2008, 9). These mixed or multi-methods research designs are merging different methods in different stages of the research ...
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Data Mining Methods for Microarray Data Analysis
2005The advent of gene expression microarray technology enables the simultaneous measurement of expression levels for thousands or tens of thousands of genes in a single experiment (Schena, et al., 1995). Analysis of gene expression microarray data presents unprecedented opportunities and challenges for data mining in areas such as gene clustering (Eisen ...
Lei Yu, Huan Liu
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