Examples of using Multivariate analysis in English and their translations into Indonesian
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Multivariate analysis showed.
A Second Generation of Multivariate Analysis.
Multivariate analysis of risk factors.
Chapter discusses the assumptions of multivariate analysis.
This multivariate analysis also supports Dr.
These variables lost significance in the multivariate analysis.
In multivariate analysis we have many observations on a finite number of variables.
Core classes include mathematical statistics, regression analysis, multivariate analysis, and experimental design.
This association held up through multivariate analysis, which controlled for the other potential contributing influences.
NICU admission varied by race and ethnicity,although these differences varied from state to state and lost significance in the multivariate analysis.
So, in summary, this multivariate analysis vindicates pretty much everything that Denise said in her July 16, 2010 post.
Data envelopment analysis provides efficiency coefficients similar to those obtained by multivariate analysis without any distributional assumption.
Multivariate analysis including factor analysis, cluster analysis, correspondence analysis; .
Structural equation modeling(SEPATH) is a very general,very powerful multivariate analysis technique that includes specialized versions of a number of other analysis methods as special cases.
Multivariate Analysis- includes factor analysis, cluster analysis, correspondence analysis, etc.
HIV infection correlated significantly with ED in univariate analysis(odds ratio, 34.19)and remained the strongest predictor of ED in multivariate analysis(odds ratio, 42.26), after adjustment for age and BMI.
Multivariate analysis identified both FUS-ERG and RUNX1-CBFA2T3 as independent risk factors with hazard ratios of 1.9( P〈 .0001) and 0.3( P= .025), respectively.
When something like this happens in a multivariate analysis, it may be due to the model not incorporating a variable that has important relationships with the other variables.
Multivariate analysis methods are used in the evaluation and collection of statistical data to clarify and explain relationships between different variables that are associated with this data.
Nancy Lynn Barrickmansaid that Brian T. Shea concluded by multivariate analysis that Bonobos are more neotenized than the common chimpanzee, taking into account such features as the proportionately long torso length of the Bonobo.
In multivariate analysis studies, nonlinearity may lead to significantly different results from those obtained through more conventional linear analyses. .
ProSensus, experts in multivariate analysis and statistical consulting to help you model, predict, and improve product quality and process efficiency.
In Mark, multivariate analysis of apparatus data from the UBS Greek New Testament(4th ed.) places P{\displaystyle{\mathfrak{P}}} 45 in a group which includes W(for chapters 5-16), Θ, Family 1, 28, 205, 565; the Sinaitic Syriac, Armenian, and Georgian versions; and Origen's quotations.
Independent predictors in the multivariate analysis showed the following to be associated with greater likelihood of NICU admission for very low birth weight babies.
A complete multivariate analysis and experimental design software that can work with numerous forms of data in order to generate reliable statistical information.
Shea found by multivariate analysis that bonobos are more neotenized than the common chimpanzees, taking into account such features as the proportionately long torso length of the bonobo.[23].
Multivariate analyses controlled for sociodemographic factors.
Multivariate analyses involve more than two variables.
In multivariate analyses the effects are usually small, but they are still there.