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Jmp 16 statistical software

Manufactured by SAS Institute
Sourced in United States

JMP 16 is a statistical software package developed by SAS Institute. It provides interactive and visual data analysis capabilities for users to explore, analyze, and interpret data. The software offers a range of statistical tools and techniques, including data visualization, modeling, and predictive analytics.

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Lab products found in correlation

3 protocols using jmp 16 statistical software

1

Swallowing Sound Index in ALS

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The data are expressed as mean ± standard deviation or median (minimum, maximum) for continuous variables and frequencies and percentages for discrete variables. Statistical analysis was performed using JMP 16 statistical software (SAS Institute Inc., Cary, NC, USA). The statistical significance of the intergroup differences was assessed using t-tests or χ2 tests, as appropriate. Baseline data of patients with ALS were analyzed, and two-step strategies were employed to assess the relative importance of the variables in their association with the swallowing sound index using multiple logistic analysis. First, a univariate analysis was performed. Subsequently, a multi-factorial analysis was performed with selected factors that had a p-value of < 0.05 in the univariate analysis and age. A p-value of < 0.05 was considered to be statistically significant.
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2

Tachycardia Changes in Aspirin and Dual Therapy

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First, the tachycardia change proportions were calculated in both the aspirin monotherapy and the dual (aspirin plus cilostazol) groups and were validated using the chi-square test. Next, baseline data and outcomes were validated among four groups: aspirin non-tachycardia changes (AN), aspirin-tachycardia changes (AT), dual-non-tachycardia changes (DN), and dual-tachycardia changes (DT). All statistical analyses were performed using the JMP 16 statistical software (SAS Institute Inc., Cary, NC, USA). The data are expressed as median±interquartile range and were analyzed using the chi-square test or nonparametric Kruskal–Wallis test. Statistical significance was set at p<0.05. According to the statistically significant data, for post-hoc analysis clearing differences among the four groups, the corresponding analysis was performed using the chi-square test, and the Steel–Dwass test was performed using the Kruskal–Wallis test.
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3

Morphometric Analysis of GAL-ir Nerve Fibers

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For the morphometric data, the brain was divided into three portions: the rostral 1/3, middle 1/3, and caudal 1/3 portions. Three to twelve sections were randomly selected from each of these portions in each of the four animals. The total length of the GAL-ir nerve fibers within the dura mater was measured in each of the various regions with a personal computer (Hewlett-Packard, Japan), a digital pencil (Wakom, Japan), and a digital tracing tablet (Wakom) by freehand drawing (Lumina Vision program, Mitani Corporation, Japan). Data about the cerebral falx, other cerebral portions, and cerebellar dura mater were obtained from 1, 3, and 14 digital images (each image size = 660 µm × 820 µm), respectively, in each section. The proportion of their length to the area of each region was calculated for immunoreactive density51 (link)–53 (link). The average of such immunoreactive density was recorded for each animal. Difference among several regions was examined by analysis of variance and Tukey’s test using the JMP® 16 statistical software (SAS Institute Inc., Cary, NC, USA).
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