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1) Multiple testing correction and FDR: In the revised manuscript, we now systematically correct for multiple testing and estimate FDR.
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This paper provided a novel method that only used chemical structures to develop efficient and stable models for testing and estimating association constants of the cesium chelates.
In this article, we propose a maximum likelihood approach for testing and estimating the imprinted effects of iQTL that contribute to variation in a quantitative trait.
Structural equation modelling represents a contemporary statistical technique for testing and estimating the relation between the factors and variables [91].
SEM is a statistical technique for testing and estimating causal relationships using a combination of statistical data and qualitative causal assumptions.
Structural equation modelling (SEM) is a statistical technique for testing and estimating such recursive relationships [ 2- 4].
Structural equation model (SEM [ 23, 24] is a statistical technique for testing and estimating causal relationships using a combination of statistical data and qualitative causal assumptions.
By using the combination of statistical data and qualitative causal assumptions, SEM technique was adopted in attempt to test and estimate causal relations.
A different design based on reciprocal backcrosses was proposed to test and estimate the distribution of iQTL responsible for physiological traits related to endosperm development in maize [16].
Additionally, for better explanation of the data, a General Linear Model (GLM) using a second-order model was applied to test and estimate the effect of musical training and the interaction with the conditional probability on EANm responses.
This approach can be used to test and estimate the causal effect between a risk factor and an outcome.
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