Each replicate served as the experimental unit for all variables (body weights, egg weights, feed intake, total dozens of eggs produced, feed conversion ratio). All performance data was evaluated for significance by one-way analysis of variance (ANOVA) at a significance level of p < 0.05 using JMP statistical software (version 15.2.1, SAS, Cary, NC, USA). If ANOVA results were significant (p < 0.05), a Tukey's multiple comparisons t-test was conducted to compare the mean of each treatment group with the mean of every other treatment at p < 0.05 significance level. The individual egg served as the experimental unit for analysis of all egg quality measurements (120 eggs per treatment, 30 eggs/replicate at each time point) and egg chemistry data (16 eggs per treatment, 4 eggs/replicate at each time point of collection) including crude fat, total cholesterol, fatty acid profile, and β-carotene content between the four treatment groups was conducted for significance by one-way analysis of variance (ANOVA) at a significance level of p < 0.05 using JMP statistical software (version 15.2.1, SAS, Cary, NC, USA).
Jmp statistical software
Manufactured by SAS Institute
Sourced in United States
JMP is a data analysis software developed by SAS Institute. It provides interactive and visually-driven statistical discovery capabilities, allowing users to explore data, build models, and uncover insights.
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Lab products found in correlation
Prism software, by GraphPad (4 mentions)
Spss statistic, by IBM (2 mentions)
Jmp pro 12, by SAS Institute (2 mentions)
Spss statistical software, by IBM (2 mentions)
Macos x, by SAS Institute (2 mentions)
Microsoft excel, by SAS Institute (1 mentions)
Phoenix winnonlin 6, by Pharsight (1 mentions)
Originpro, by OriginLab (1 mentions)
Egm 2, by R&D Systems (1 mentions)
Vascular endothelial growth factor (vegf), by R&D Systems (1 mentions)
Egm 2, by Lonza (1 mentions)
Sas proc glimmix procedure, by SAS Institute (1 mentions)
Stata statistical software, by StataCorp (1 mentions)
Sigmaplot, by Grafiti LLC (1 mentions)
Odyssey clx imaging system, by LI COR (1 mentions)
R version 3, by R Project for Statistical Computing (1 mentions)
Matlab 2016a, by MathWorks (1 mentions)
Jmp pro 10, by SAS Institute (1 mentions)
Stata statistical software version 13, by StataCorp (1 mentions)
Spss statistics for window, by IBM (1 mentions)
341 protocols using jmp statistical software
1
Egg Production and Quality Analysis
2
Whey vs. Casein Protein Effects
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Data are reported as mean ± standard error of the mean. Each outcome was compared between the experimental (whey) and control (casein) groups using Mann–Whitney U test, using JMP statistical software (ver. 14.0: SAS Institute, Cary, NC, USA). When p < 0.05, the differences were considered statistically significant, and when 0.05 < p < 0.10, the differences were considered marginally significant.
3
Zoosporic Germination Response to ZE Dilution
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Data were analyzed using JMP statistical software (version 9.0, SAS Institute Inc., Cary, NC, United States). Analysis of variance (ANOVA) was conducted to analyze treatment effects. Mean separation was performed using Fisher’s protected least significant difference. An alpha level of 0.05 was used for all analysis. In analyzing the relationship between zoosporic germination and the concentration of ZE dilution factors, regression was performed by combining the data of two independent trials, with each having three replicates. All the experiments were conducted twice. If there was no interaction between repeated trials (P > 0.05), data were combined from all trials.
4
Comparative Gene Expression Analysis
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All statistics were performed using ANOVA on rank transformed data using JMP statistical software (SAS Institute, Cary, NC). Differences between dietary conditions were evaluated using delta-Ct’s, with dietary condition, fraction, timepoint, and subject as factors. Within each dietary condition, differences in gene expression between fractions were evaluated on delta-Ct’s, using fraction, timepoint, and subject as factors.
5
Prognostic Value of High-Sensitivity Troponin
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The distribution of baseline characteristics for categorical variables is expressed as percentage frequency. Continuous variables are described as means and standard deviations or as medians and interquartile ranges, as appropriate. Differences among groups were detected using Pearson χ2 test and Fisher's exact test for categorical variables and Mann-Whitney test for continuous variables.
Event rates at 30 and 180 days were stratified by guideline-based cTnI and hsTnT 99th percentile reference limits (0.4 ng/mL and 14 ng/L respectively). Cox regression analysis was used to evaluate the relation between hsTnT and outcome. Adjusted analyses took into account all the remaining elements of the TIMI risk score [19 (link)] including age, recent aspirin use, ≥3 CV risk factors, known coronary disease, ST segment deviation and repeated episodes of rest angina in the last 24 h. The differences in endpoints were analyzed with the log-rank test and expressed as Kaplan Meier curves. A p value<0.05 was considered statistically significant.
All statistical analyses were performed with JMP statistical software (version 11.0.0, SAS Institute Inc., Cary, North Carolina, USA) and SPSS Statistics (version 20, IBM Corporation, Armonk, NY, USA).
Event rates at 30 and 180 days were stratified by guideline-based cTnI and hsTnT 99th percentile reference limits (0.4 ng/mL and 14 ng/L respectively). Cox regression analysis was used to evaluate the relation between hsTnT and outcome. Adjusted analyses took into account all the remaining elements of the TIMI risk score [19 (link)] including age, recent aspirin use, ≥3 CV risk factors, known coronary disease, ST segment deviation and repeated episodes of rest angina in the last 24 h. The differences in endpoints were analyzed with the log-rank test and expressed as Kaplan Meier curves. A p value<0.05 was considered statistically significant.
All statistical analyses were performed with JMP statistical software (version 11.0.0, SAS Institute Inc., Cary, North Carolina, USA) and SPSS Statistics (version 20, IBM Corporation, Armonk, NY, USA).
6
Prognostic Value of Urinary Na/K Ratio
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Data were presented as the mean ± standard deviation, median (interquartile range), or percentages, as appropriate. Event frequencies were compared using the chi-square test. Other data comparisons between two groups were performed using the Student’s t-test or the Mann–Whitney U test, as appropriate. The optimal Na/K ratio cutoff point was determined by receiver operating characteristic (ROC) curve analysis. Outcomes were displayed using Kaplan–Meier curves and compared using log-rank tests. The prognostic values of the Na/K ratio and clinical variables were analyzed using Cox proportional hazards models and hazard ratios (HRs) were described with a 95 % confidence interval (CI). For multivariable analyses, the Na/Cr ratio in spot urine (used in a previous study [14] (link)), left ventricular ejection fraction, or the use of diuretics were used for adjustments. Statistical significance was set at p < 0.05. All analyses were performed using the JMP statistical software (version 11; SAS Institute, Cary, NC, USA).
7
Comparative Statistical Analysis of Groups
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For comparisons between quantitative variables between several groups, Kruskal–Wallis test was performed, and whenever significant it was followed by Mann–Whitney U test for each pair. Chi-squared test was conducted to test for differences between categorical variables with Fisher’s exact test applied when appropriate. For paired quantitative variables Wilcoxon signed rank test was used. All statistical analyses including national cut-off calculations were conducted using JMP statistical software (SAS Institute, Cary, NC, USA). All p-values <0.05 were considered significant.
8
CTC Counts and Survival Analysis
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Associations between CTC counts and clinicopathological findings were analyzed using a t‐test. RFS was defined as the time from surgery to recurrence or death from any cause. RFS curves were estimated by the Kaplan–Meier method and compared using the log‐rank test. Univariate and multivariate analysis was performed using the Cox proportional hazards model. All statistical analyses were performed using JMP statistical software (version 8.0; SAS Institute). A two‐sided probability (p) value of <0.05 was considered to be statistically significant.
9
Quantifying Sports Performance Metrics
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Data processing was performed in MATLAB and statistics were performed in JMP statistical software (SAS Institute Inc., Cary, NC, USA). Data are displayed as mean ± standard deviation (SD). Inter-rater (K.E. and N.L) reproducibility of the Bioharness data was evaluated by means of Bland–Altman plots [14 (link)] and interclass correlations (ICC), which were considered good reproducibility if the ICC was 0.5–0.75 and excellent reproducibility when above 0.75 [20 (link)]. One-way ANOVA was used to examine outcome variables (HR and activity) across the duration of scrimmages. A two-way (offense vs. defense and non-skill vs. skill) ANOVA was used to examine the outcome variables across the duration of scrimmages. A two-way (offense vs. defense and non-skill vs. skill) ANOVA was used to determine differences in demographic and outcome variables between groups, with post-hoc Bonferroni tests used where appropriate. Statistical significance was set at p < 0.05.
10
Serum Ionized Calcium Derangements and Mortality
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We tested the normality of continuous variables using the Shapiro-Wilk test. We presented continuous variables as mean ± standard deviation (SD) for normally distributed data, or median (interquartile rate (IQR)) for skewed data. We compared continuous variables using analysis of variance for normally-distributed data, or the Kruskal-Wallis test for skewed data. We presented categorical variables as frequency (percentage) and compared them using the chi-squared test. We obtained the mortality’s odds ratio (OR) for in-hospital serum ionized calcium derangements, compared with the persistently normal serum ionized calcium group, using logistic regression analysis. We adjusted OR for age, sex, race, principal diagnoses, comorbidities, estimated glomerular filtration rate, acute kidney injury, kidney replacement therapy, intensive care unit admissions, the number of in-hospital serum ionized calcium measurements, length of hospital stay, and admission serum ionized calcium. We considered a two-tailed p-value less than 0.05 as statistically significant. We performed all analyses using JMP statistical software (Version 10; SAS Institute Inc., Cary, NC, USA).
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