R statistical software

Manufactured by IBM

Sourced in United States

R is an open-source software environment for statistical computing and graphics. It provides a wide variety of statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and more.

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R statistical software (version 3.6.2). R statistical software (version 3.6.3) R statistical software v4.0.3 Statistical Software R version 4.0.0 R” statistical computing software version 3.1.1 R studio Statistical Software R software

69 protocols using r statistical software

Analyzing Immunotherapy Adverse Events

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Hazard ratios (HRs) and their 95% confidence intervals were estimated through the Cox regression proportional model; in the multivariate approach, a forward stepwise procedure was used, and the enter and remove limits were set to 0.05 and 0.10, respectively. The association of irAE frequency with biological parameters with clinical outcomes in the two patient cohorts was assessed by the chi-square test. Statistics were performed by the SPSS software 23.0 (International Business Machines Corp., New York, NY, USA) and R statistical software.

Fameli A., Nardone V., Shekarkar Azgomi M., Bianco G., Gandolfo C., Oliva B.M., Monoriti M., Saladino R.E., Falzea A., Romeo C., Calandruccio N.D., Azzarello D., Giannicola R., Pirtoli L., Giordano A., Tassone P., Tagliaferri P., Cusi M.G., Mutti L., Botta C, & Correale P. (2022). PD-1/PD-L1 immune-checkpoint blockade induces immune effector cell modulation in metastatic non-small cell lung cancer patients: A single-cell flow cytometry approach. Frontiers in Oncology, 12, 911579.

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Survival Analysis of Heart Failure Patients

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Quantitative variables are expressed as mean ± SD or median or percentile 25 and 75 as required. Categorical variables are expressed as numbers and percentages. A Student's t˗test or the Mann–Whitney U test were used to compare continuous variables, and a χ² test or the Fischer's exact test were used to compare categorical variables. A Cox proportional‐hazards model was used to calculate hazard ratios (HR). For the multivariate analysis, variables with a P‐value greater than 0.10 were removed from the model. Event‐free survival rates were estimated by the method of Kaplan–Meier and compared by the two‐stage hazard rate comparison method⁹ and the log‐rank test. Analyses were performed with SPSS Statistics for Windows (IBM SPSS Version 25.0. Armonk, NY: IBM Corp.) and R statistical software (A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R‐project.org/).

Vermeersch G., Abugattas J., Varnavas V., De Cocker J., Schwagten B., Sieira J., de Asmundis C., Chierchia G, & De Greef Y. (2021). Efficacy and safety of the second‐generation cryoballoon ablation for the treatment of persistent atrial fibrillation in elderly patients. Journal of Arrhythmia, 37(3), 626-634.

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Predictive Nomogram for Intraoperative Adverse Events

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Quantitative data was described as mean ±SD or median (25th–75th); qualitative data was described as n (%). The comparisons between groups for qualitative variables were performed by Chi-square test or Fisher exact test and comparisons between groups for quantitative variables was performed using a t-test or Wilcoxon test. The likelihood ratio test with backward step-down selection was used for the multivariate logistic analysis. The VIFs and Tolerance value were calculated using the “car” package. The ROC curves were plotted using the “pROC” package. Nomogram construction and calibration plots were performed using the “rms” package. A two-sided P value <0.05 was considered statistically significant. The cut-off probability threshold of the nomogram for the prediction of IAC was determined by maximizing the Youden index. The statistical analysis was conducted using R statistical software (version 3.3.1) and SPSS software for Windows, version 20.0 (IBM, Armonk, NY, USA).

Sun Y., Wang B., Bi K., Meng X., Zhang L, & Sun X. (2020). The combined nomogram based on the CT features may be used as a complementary method of frozen sections to predict invasive lung adenocarcinoma manifesting as ground-glass nodules. Journal of Thoracic Disease, 12(5), 2361-2371.

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Statistical Analysis of Nomogram Model

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Statistical analyses were performed using R statistical software (V4.2.1), IBM SPSS Statistics (V21.0), and Python programming software (V3.7.1). The normally distributed variables were recorded as mean (standard deviation), and compared using the Student’s t-test. All non-normally distributed variables were recorded as [interquartile range (IQR)], and compared using Mann–Whitney U-test. The categorical characteristics were recorded as number (percentage), and compared using the χ² test. A two-sided P <0.05 was regarded as the statistically significant difference. In the validation of the nomogram model, the receiver operating characteristic (ROC) curve, calibration curve with 1000 bootstrap samples, Hosmer-Lemeshow (HL) test, and decision curve analysis (DCA) was used to evaluate the discrimination, calibration, goodness-of-fit, and clinical usefulness of the nomogram model, respectively.

Meng F., Wu Q., Zhang W, & Hou S. (2023). Shear-Wave Elastography-Based Radiomics Nomogram for the Prediction of Cardiovascular Disease in Patients with Diabetic Kidney Disease. Diabetes, Metabolic Syndrome and Obesity, 16, 2705-2716.

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Statistical Analysis of Research Data

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Statistical analyses were performed with SPSS (version 27, IBM Corp, Armonk, NY, United States) and R statistical software (version 3.6.0, Vienna, Austria). A Student's t‐test was used for continuous variables. A p‐value of < .05 was considered statistically significant.

Sogade O.O., Aben R.N., Eyituoyo H., Arinze N.C, & Sogade F.O. (2021). Feasibility study for echocardiography‐guided lead insertion for permanent cardiac implantable electronic devices. Pacing and Clinical Electrophysiology, 44(8), 1365-1370.

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Statistical Analysis of Research Data

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Descriptive statistics was presented as frequencies and percentages for categorical data whereas medians and interquartile ranges for continuous data. All analyses were performed using the R statistical software and SPSS (IBM Version 20).

Saleh M., Sharma K., Shah J., Karsan F., Waweru A., Musumbi M., Shah R., Sayed S., Abayo I., Karimi N., Gondi S., Rupani S., Kirathe G, & Amariati H. (2022). A pilot phase Ib/II study of whole-lung low dose radiation therapy (LDRT) for the treatment of severe COVID-19 pneumonia: First experience from Africa. PLoS ONE, 17(7), e0270594.

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Determinants of COVID-19 Vaccine Uptake Among Healthcare Workers

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A chi-square test was used to test the differences in the proportion of vaccine confidence, willingness and vaccination uptake among the different demographic groups. Logistic regression models were applied to the total sample and each HCW sub-group separately to detect the different patterns of the relationship between vaccine confidence (X) and willingness (Y). Demographic characteristics were introduced into logistic regression model as covariates. Odds ratio (OR) and 95% confidence interval (CI) were used for detection of the strength of association between study variables.
Participants were further categorized into willing & vaccinated, willing & unvaccinated, unwilling & vaccinated, or unwilling & unvaccinated groups to explore the factors relating to lack of vaccination among the willing population. A logistic regression model was further applied among participants that reported willingness to get vaccinated to explore the effects of vaccine confidence on actual vaccination uptake. The odds ratio (OR) and 95% confidence interval (CI) were also calculated and displayed. SPSS (version 22.0, IBM, Armonk, NY, USA) and R statistical software (version 3.6.3; appendix p 11) were used for cleaning up the data and statistical analysis. The significance level was considered when the p value was less than 0.05.

Wang C., Wang Y., Han B., Zhao T.S., Liu B., Liu H., Chen L., Xie M., Zheng H., Zhang S., Zeng J., Huang N.H., Du J., Liu Y., Lu Q.B, & Cui F. (2021). Willingness and SARS-CoV-2 Vaccination Coverage among Healthcare Workers in China: A Nationwide Study. Vaccines, 9(9), 993.

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Multivariate Analysis of Cytokine Profiles

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In order to find correlations among cytokine profile groups and APO, a Factorial analysis of mixed data (FAMD) was performed that combined Principal Component Analysis (PCA) for continuous variables and Multiple Correspondence Analysis (MCA) for categorical variables (Audigier et al., 2016 (link)). Kruskal-Wallis/Mann-Whitney U test was used to compare the cytokines between the different groups. One-way ANOVA with Dunnett’s post-hoc test was performed to compare the relationship between cytokine/IFN-γ among groups. Spearman rank based pairwise correlation analysis was performed to analyze cytokine abundances in all the groups. R statistical software and IBM-SPSS version 23 were used for all analyses. Heatmaps were made using Morpheus, https://software.broadinstitute.org/morpheus.

Gómez L.A., De Avila J., Castillo D.M., Montenegro D.A., Trujillo T.G., Suárez L.J, & Lafaurie G.I. (2020). Porphyromonas gingivalis Placental Atopobiosis and Inflammatory Responses in Women With Adverse Pregnancy Outcomes. Frontiers in Microbiology, 11, 591626.

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Sepsis Outcomes: Descriptive Analysis

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We will use a combination of IBM SPSS Statistics and R Statistical Software for all analyses. We will start with descriptive analyses on baseline characteristics (age, sex, comorbidities, vital sign measurements and other clinical features, blood tests results, baseline EQ5D-5L score), final diagnosis, hospital admission, ICU admission, length of stay, EQ5D-5L compared to baseline, and 30-day mortality. Results will be stratified based on whether patients do or do not meet the primary outcome sepsis.

Loots F.J., Hopstaken R., Jenniskens K., Frederix G.W., van de Pol A.C., Van den Bruel A., Oosterheert J.J., van Zanten A.R., Smits M, & Verheij T.J. (2020). Development of a clinical prediction rule for sepsis in primary care: protocol for the TeSD-IT study. Diagnostic and Prognostic Research, 4, 12.

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Statistical Analysis of Research Data

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All statistical analysis was performed via the R statistical software (R version 4.1.3) and IBM SPSS Statistics (Version 25.0). Normally distributed continuous variables are described as means with standard deviations (SD). The median (M) with interquartile range (IQR, 1st quartile, 3rd quartile) and nonparametric Wilcoxon signed-rank tests were applied for variable description and comparison, respectively. The categorical variables are reported as the numbers and percentages of patients in each category. Proportions were compared by the Pearson’s Chi-square test. The correlation analysis was performed with Spearman non-parametric correlation tests. All graphs were delineated using GraphPad Prism 8 software (GraphPad Software Inc., San Diego, CA, USA). A value of P < 0.05 was considered statistically significant.

Zhang W., Liu S., Miao L., Fu A., Bao J., Zheng L., Li E., Yu J, & Wang Y. (2023). Dynamics of CD4+ T-Cells and Neutralizing Antibody Responses to Three Consecutive Doses of Inactivated COVID-19 Vaccines in PLWH. Infection and Drug Resistance, 16, 2695-2707.

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