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The bioactivity between bovine and human IL-10 was compared using a univariate general linear model: cytokine production = IL-10 source (bovine or human) * IL-10 concentration.
Using a univariate general linear model, statistical differences between the incidences over time were calculated.
Unsatisfactory rates were first compared using a univariate general linear model in SPSS V.19.
Statistical analysis Differences in demographic data and risk factors between control participants and those with type 2 diabetes were analysed using a univariate general linear model or logistic regression adjusting for age and sex.
The differences between the means of the groups were tested using a univariate general linear model with adjustments for age, and categorical data were analyzed by using the χ test.
Adjustment of variables was carried out using a univariate general linear model; the variable to be adjusted was the dependent variable and the group (control, SMI, or absence of SMI) the independent variables.
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Using a univariate approach these parameters were optimized.
First, the PLE conditions were optimized using a univariate approach.
Experimental parameters were optimized using a univariate experimental design.
In addition, the prognostic value of GNA13 expression for OS and DFS was analyzed using a univariate analysis model on these clinialpathological parameters (Tables 2 and 3).
We propose the Intersection method that is simple to implement, using a univariate hotspot detection method.
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