For statistical analysis of the comparison data, data normality was assessed by the Kolmogorov-Smirnoff test and Pearson correlation coefficients (r) were calculated using SPSS 18 software (IBM). The level of agreement between serum and DBS methods was assessed using Bland-Altman plot values (bias and limits of agreement as Ϯ SD 1.96); means and SD were calculated using Microsoft Excel 2010 (Microsoft Corporation) and SPSS 18 software (IBM). Deming regression parameters were calculated using the R statistical software environment (http://www.r-project.org) and the MethComp package.
Spss 18
SPSS 18.0 is a statistical software package designed for data analysis. It provides a wide range of data management and analysis capabilities, including descriptive statistics, advanced statistical modeling, and data visualization tools. The software is intended to help users analyze and interpret data effectively.
Lab products found in correlation
998 protocols using spss 18
Evaluation of recGH/pitGH Ratios in Serum and DBS
For statistical analysis of the comparison data, data normality was assessed by the Kolmogorov-Smirnoff test and Pearson correlation coefficients (r) were calculated using SPSS 18 software (IBM). The level of agreement between serum and DBS methods was assessed using Bland-Altman plot values (bias and limits of agreement as Ϯ SD 1.96); means and SD were calculated using Microsoft Excel 2010 (Microsoft Corporation) and SPSS 18 software (IBM). Deming regression parameters were calculated using the R statistical software environment (http://www.r-project.org) and the MethComp package.
Dietary Patterns and Metabolic Outcomes
A paired sample t-test was conducted to compare the changes before and after intervention within groups. Differences in response among groups were analyzed via one-way ANOVA, where results are presented as means and standard deviations. Duncan’s post hoc test was performed for multiple comparisons when changes were significantly different among groups.
The dietary results were analyzed via principal component analysis (PCA) with the correlation matrix as input [21 (link)]. The Kaiser-Meyer-Olkin (KMO) value was greater than 0.6, and results were considered significant at p < 0.001. The associations between interventional effects (including dietary patterns and PG) and sociodemographic factors were assessed according to the odds ratio (OR) with the logistic regression model [22 (link)]. The final model included those variables that showed a statistical significance of up to 5% (p < 0.05). All statistical procedures were performed using SPSS 18.0 software (IBM, New York, NY, USA).
Developing a Validated Qualitative Interview Scale
Validity and Reliability of TB Questionnaire
Triplicate Biological Replicates Analysis
Spatial Mapping of PAH Exposure Risk
Comparative Analysis of Protein Expression
Fingerprinting and Genotyping of Mycobacterium tuberculosis
Pear Cultivars Antioxidant Evaluation
Statistical Analysis of Experimental Data
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