The largest database of trusted experimental protocols

Jmp pro 14.2.0 statistical software

Manufactured by SAS Institute
Sourced in United States

JMP Pro 14.2.0 is a statistical software package developed by SAS Institute. It provides data analysis and visualization tools for researchers and analysts. The software enables users to explore, model, and analyze data through a variety of statistical methods.

Automatically generated - may contain errors

Lab products found in correlation

2 protocols using jmp pro 14.2.0 statistical software

1

Cardiac Rehabilitation Outcomes Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols
Serum BNP and NT-pro-BNP levels are expressed as median and interquartile range because they showed non-parametric distributions. Other continuous values were expressed as mean±standard deviation. Student’s t-tests or Mann-Whitney U tests were used for comparison of continuous variables between groups. Categorical variables are reported as number (proportion, %) and compared using Pearson’s chi-square tests. Event rates for the primary endpoint were estimated with Kaplan-Meier curves and compared with a log-rank test. A Cox proportional hazard regression model was used to assess predictors of the primary endpoint. Additionally, a propensity-matched analysis was used to examine the effect of outpatient cardiac rehabilitation on the primary endpoint. A multivariate logistic regression model was used to calculate the propensity score, and 2 cohorts were created based on the score for the comparison. All analyses were performed using JMP Pro 14.2.0 statistical software (SAS Institute Inc., NC, USA). A P-value of <0.05 was considered statistically significant.
+ Open protocol
+ Expand
2

Survival Analysis of Surgical Outcomes

Check if the same lab product or an alternative is used in the 5 most similar protocols
Recurrence-free-survival (RFS) and overall survival (OS) were calculated from the date of surgery to the date of recurrence, the date of death from any cause, or the date of last follow-up. To determine the appropriate cut-off values, we used receiver operating characteristic (ROC) curves and determined the area under the curve (AUC). Differences between groups were determined using t-tests in the case of normally distributed variables or by the Wilcoxon rank-sum test in the case of abnormally distributed variables for examining differences in continuous variable distributions, and Pearson’s chi-square tests for categorical variables. RFS probabilities were compared for various categories of interest using the Kaplan–Meier method with the log-rank test.
Prognostic factors were assessed with univariate and multivariate analyses, using Cox’s proportional hazards model. Hazard ratios (HR) with 95% confidence intervals (CIs) were calculated. P < 0.05 was considered to indicate statistical significance.
All statistical analyses were performed using the JMP Pro 14.2.0 statistical software (SAS Institute Inc., Cary, NC, USA) and GraphPad Prism Version 8.4.2 (GraphPad Software, San Diego, CA, USA).
+ Open protocol
+ Expand

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required

Sign up now

Revolutionizing how scientists
search and build protocols!