This study was a retrospective, single-center database study based on the histological diagnosis of CRC. Inclusion criteria included all patients diagnosed with primary CRC between 2006 and 2012 at the King Khalid University Hospital, KSA. Data including patient demographics; location of primary tumor; tumor, node, and metastasis (TNM) staging at presentation and grading; surgical intervention; disease-free period and recurrence; and final status of the patient at last follow-up were collected. Descriptive statistics were analyzed using JMP 11 statistical software (SAS Institute Inc, Cary, NC, USA). In this study, we used a marginal structural model to understand whether metastasis location and timing had an effect on the survival rate. Probability of metastasis was predicted using age, stage, site, and vascular invasion. The inverse of these probabilities were used as weights to construct an exponential survival model adjusted for metastasis location (lungs, liver, or both).
Jmp 11 statistical software
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Sourced in United States
JMP 11 is a statistical software package developed by SAS Institute. It provides a range of data analysis and visualization tools. The core function of JMP 11 is to enable users to explore, analyze, and model data using various statistical methods.
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10 protocols using jmp 11 statistical software
1
Retrospective Study of Colorectal Cancer
2
Progression-Free and Overall Survival
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Progression-free survival (PFS) was defined as the time from the first administration of the nab-paclitaxel regimen to the date of confirmation of disease progression or death. Overall survival (OS) was defined as the time from the first administration of the nab-paclitaxel regimen until death. Data for patients with unavailable information regarding death or disease progression were censored at the date of the last assessment.
The median probabilities for PFS and OS were estimated by the Kaplan–Meier method. The time-to-event outcomes were compared using log-rank tests. All analyses were performed using JMP 11 statistical software (SAS Institute, Cary, NC).
The median probabilities for PFS and OS were estimated by the Kaplan–Meier method. The time-to-event outcomes were compared using log-rank tests. All analyses were performed using JMP 11 statistical software (SAS Institute, Cary, NC).
3
Perioperative nausea and vomiting management
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Preventive care was based on the consensus guidelines for managing PONV from the
Society for Ambulatory Anesthesiology (SAMBA).4 (link) Although the combination of a 5-hydroxytryptamine (5-HT3) receptor
antagonist and dexamethasone is recommended as first-line therapy in the SAMBA
guideline,4 (link) 5-HT3 receptor
antagonists are not authorized by health insurance in Japan for preventing PONV. Therefore, we
selected combination administration of 0.025 mg/kg of droperidol and 0.06 mg/kg of
dexamethasone at the end of the surgery in this study.
Information on the following variables was retrieved from the medical records for
analysis: sex, age at the time of surgery, body weight at the time of surgery, and duration of
anesthesia. These variables were compared between patients with and those without PONV using
the chi-squared or Mann–Whitney U test as appropriate for the data. The level of statistical
significance was set at p=0.05. Multiple logistic regression was performed to identify risk
factors for PONV. The presence or absence of PONV was the dependent variable and the remaining
variables were explanatory factors. These variables were entered into a model using the
stepwise method, with p=0.2 as the criterion for inclusion or exclusion of a factor.
Statistical analyses were performed using JMP-11 statistical software (SAS, Tokyo, Japan).
Society for Ambulatory Anesthesiology (SAMBA).4 (link) Although the combination of a 5-hydroxytryptamine (5-HT3) receptor
antagonist and dexamethasone is recommended as first-line therapy in the SAMBA
guideline,4 (link) 5-HT3 receptor
antagonists are not authorized by health insurance in Japan for preventing PONV. Therefore, we
selected combination administration of 0.025 mg/kg of droperidol and 0.06 mg/kg of
dexamethasone at the end of the surgery in this study.
Information on the following variables was retrieved from the medical records for
analysis: sex, age at the time of surgery, body weight at the time of surgery, and duration of
anesthesia. These variables were compared between patients with and those without PONV using
the chi-squared or Mann–Whitney U test as appropriate for the data. The level of statistical
significance was set at p=0.05. Multiple logistic regression was performed to identify risk
factors for PONV. The presence or absence of PONV was the dependent variable and the remaining
variables were explanatory factors. These variables were entered into a model using the
stepwise method, with p=0.2 as the criterion for inclusion or exclusion of a factor.
Statistical analyses were performed using JMP-11 statistical software (SAS, Tokyo, Japan).
4
Evaluating Treatment Response Groups
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We assigned patients with partial response and clinical remission into group 1, and patients with no response into group 2. For the statistical analysis of the data, JMP 11 statistical software (SAS Institute Inc., Cary, NC, USA) was used. The differences of demographic data, serum laboratory data, and imaging findings between groups 1 and 2 were assessed by using chi-square test and Student’s t-test or Mann-Whitney U-test in data sets that were not normally distributed. A p-value of <0.05 was considered statistically significant.
5
Tongue Pressure and Swallowing Dysfunction
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The data were expressed as the mean ± standard deviation or the median (minimum, maximum) for continuous variables and frequencies and percentages for discrete variables. Statistical analysis was performed using JMP 11 statistical software (SAS Institute Inc., Cary, NC, USA). The statistical significance of intergroup differences was assessed using t-tests or χ2 tests as appropriate. The baseline data in the stroke patients were analyzed, and two-step strategies were employed to assess the relative importance of variables in their association with tongue pressure using least square linear regression analysis. First, a univariate analysis was performed. Then, a multi-factorial analysis was performed with selected factors that had p<0.20 on univariate analysis. Receiver operating characteristic (ROC) analysis was performed to determine the tongue pressure predicting a modified MASA score <95, which suggests swallowing dysfunction. Kaplan–Meier and Cox proportional hazard regression analyses were performed to test the difference in the development of pneumonia between the high and low tongue pressure groups. A univariate split-plot approach was utilized for changes in tongue pressure over time, with the last observation carried forward for missing data. We considered p<0.05 as statistically significant.
6
Statistical Analysis of Rotator Cuff Outcomes
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JMP11 statistical software (SAS Institute, Cary, NC, USA) was used for statistical analyses. The Wilcoxon signed-rank test was used to compare between-group JOA scores pre- and postoperatively. Univariate logistic analysis was used to compare the relationship between the clinical parameters of the satisfactory and unsatisfactory groups and to analyze the relationship between the Goutallier stage in the rotator cuff muscles and sections in the JOA score. Multivariate logistic analysis using a stepwise technique was performed to evaluate the significant parameters affecting “satisfactory” or “unsatisfactory” outcomes in the JOA score, along with the odds ratio (OR) with 95% confidence intervals (CIs). Receiver operating characteristic (ROC) curve analysis was performed to obtain the cutoff value of the parameters affecting the clinical outcome. Data were expressed as mean values with standard deviations. P values < 0.05 were considered statistically significant.
7
Factors Affecting Positive Pancreatic Lesion Cytology
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The differences between continuous and categorical variables were identified using the Mann-Whitney U test and the chi-squared test or Fisher's exact test, respectively. The factors affecting positive PLC were analyzed using binomial logistic regression analyses, and the identified factors were compared using the chi-squared test or Fisher's exact test, at the p < 0.01 level, to determine factors independently associated with positive PLC. Multivariate analyses were performed for both preoperative and pathological findings.
All data were expressed as the total number of patients and proportion of the population (%). The p-values < 0.05 were considered significant. All analyses were performed using the JMP 11 statistical software (SAS Institute Inc., Cary, NC, USA).
All data were expressed as the total number of patients and proportion of the population (%). The p-values < 0.05 were considered significant. All analyses were performed using the JMP 11 statistical software (SAS Institute Inc., Cary, NC, USA).
8
Dosimetric Impact of CTV-PTV Margins
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CI and HI comparisons based on 3- and 5-mm CTV–PTV margins were made using the paired t-test or Wilcoxon signed-rank test, depending on sample normality (Shapiro–Wilk test). Dose coverage change comparisons for the CTV with two types of CTV–PTV margins were made using the paired t-test. Similarly, dose coverage change comparisons with different dose fractions and marker–tumor distances were made using the Tukey–Kramer test. Multiple regression analysis was performed to determine whether the CTV–PTV margin, dose fraction, and marker–tumor distance were independently associated with ∆CTV D2, D95, D99 and ∆TCP. To predict ∆CTV D2, D95, D99 and ∆TCP distributions, regression analyses were performed on 95th percentile values. A linear regression was also performed between ∆TCP and ∆CTV D2, D95 and D99. All statistical analyses used JMP® 11 statistical software (SAS Institute Inc., Cary, NC, USA). P < 0.05 indicated statistical significance.
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CI and HI comparisons based on 3- and 5-mm CTV–PTV margins were made using the paired t-test or Wilcoxon signed-rank test, depending on sample normality (Shapiro–Wilk test). Dose coverage change comparisons for the CTV with two types of CTV–PTV margins were made using the paired t-test. Similarly, dose coverage change comparisons with different dose fractions and marker–tumor distances were made using the Tukey–Kramer test. Multiple regression analysis was performed to determine whether the CTV–PTV margin, dose fraction, and marker–tumor distance were independently associated with ∆CTV D2, D95, D99 and ∆TCP. To predict ∆CTV D2, D95, D99 and ∆TCP distributions, regression analyses were performed on 95th percentile values. A linear regression was also performed between ∆TCP and ∆CTV D2, D95 and D99. All statistical analyses used JMP® 11 statistical software (SAS Institute Inc., Cary, NC, USA). P < 0.05 indicated statistical significance.
9
Isocentric Dose Delivery Evaluation
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As isocentric radiation beams intersect at a single isocenter and have low dosimetric uncertainty, doses measured after isocentric dose delivery were used as controls. By contrast, doses measured using non-isocentric dose delivery were divided into two groups of smaller PE (SPE) and larger PE (LPE) by using their median PE value. Snedocor's F-test was used to compare the range of dose differences in each group. Relationships in the dose differences between PE values and dose heterogeneity were determined using Pearson correlation analysis or Spearman rank correlation analysis depending on sample normality (Shapiro–Wilk test). P < 0.05 was considered significant. All statistical analyses were performed using JMP® 11 statistical software (SAS Institute Inc., Cary, NC, USA).
10
Dominant Eye Analysis in Patients
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The statistical analysis of the data was conducted using the JMP 11 statistical software (SAS Institute, Cary, NC, USA). Normality of data was assessed by evaluation of the histogram plots, and correlation parameters were calculated using Pearson or Spearman analysis, where appropriate. The dominant eye was noted in the patient history, and correlations between the dominant and contralateral, as well as between the right and left eye, were assessed. The dominant eye was selected for further analysis.
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