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Rstudio program

Manufactured by Posit
Sourced in United States, Austria

RStudio is an Integrated Development Environment (IDE) for the R programming language. It provides a user-friendly interface for writing, running, and debugging R code. RStudio includes features such as a code editor, a console, and tools for data visualization and analysis.

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12 protocols using rstudio program

1

Validation of Research Questionnaire Scale

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Evidence of content validity was analyzed using Aiken’s V coefficient [37 ]. Descriptive analysis and exploratory factor analysis (EFA) were performed with the Factor Analysis Program, version 10.1. Furthermore, the mean, standard deviation, skewness, and kurtosis were analyzed for the 14 items of the scale by considering a skewness and kurtosis coefficient of −2 [38 ] and the Kaiser–Meyer–Olkin coefficient (KMO) and Bartlett’s test for EFA. Consequently, parallel analysis suggested the existence of two factors, and the estimation method was unweighted least squares with prominent rotation.
For the confirmatory factor analysis (CFA), the RStudio program was used. Structural equation modeling was considered, and the comparative fit index (CFI) and the Tucker–Lewis Index (TLI) were analyzed. Additionally, the parameters for the root mean square error of approximation (RMSEA) and the root mean square error rate were taken into account as per the criteria proposed by Hu and Bentler [39 (link)], who stated that the TLI and CFI should be >0.9 and the RMSEA should be <0.08. Finally, concurrent validity was analyzed using Pearson’s correlation coefficient, and the reliability of the scale was calculated using the SPSS version 25.0 statistical program and its respective confidence intervals [40 ].
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2

Statistical Analysis of Genetic Determinants

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All statistical analyses were performed using GraphPad Prism software version 8.0 (GRAPH PAD Software Inc, San Diego, CA, USA). To determine the relationship between phenotypic and genetic determinants, the chi-square Pearson test was used. All correlation analyses were calculated using Pearson correlation. The occurrence of genes was marked as “1” when the gene was present, and “0” when it was absent, in which case the results of the Pearson correlation are identical to the point–biserial correlation. Results were considered statistically significant at p < 0.05. The R statistical platform (https://www.r-project.org) (accessed on 13 September 2022) and RStudio program (https://rstudio.com/) (accessed on 13 September 2022) were used for large-scale analysis and data visualization.
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3

Varietal Grape Pomace Characterization

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Analyses of variance and Fisher’s least significant difference (LSD) test were performed using the Statgraphics Centurion XVIII software (Statgraphics Technologies, Inc., The Plains, VA, USA) to determine the differences between the varietal grape pomace extracts. Principal component analysis (PCA) was carried out to study the association between variables and to determine similarities or differences between the varietal grape pomace extracts, using the RStudio program (R-Studio Inc., Version 2023.06.0, Boston, MA, USA).
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4

Assessing Publication Bias in Meta-Analysis

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As this review included more than 10 studies, publication bias was assessed using a funnel plot, which showed some asymmetry, prompting Egger test.[14 (link)] In case of suspected publication bias, the meta-analysis results were adjusted using the fail-safe N test[15 (link)] or the trim and fill method.[16 (link)] The assessment was performed using the R software (Version 4.1.1; R Foundation for Statistical Computing, Vienna, Austria) and the R Studio program (Version 1.4.1106; Integrated Development for R, R Studio, PBC, Boston, MA) with the “meta” package as the default setting.
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5

Biomechanical Comparison of Backup Fixation Strategies

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Mean failure load, displacement, and stiffness values were compared between backup fixation groups without primary fixation (no simulated graft and IS) and those with primary fixation (with simulated graft and IS) using 1-way analysis of variance followed by Bonferroni-adjusted post hoc pair-wise comparisons. The significance level was set a priori at α = .05. A power analysis was performed and the available sample was determined to be adequate to detect a difference of 100-N force in failure load at a power of 86%. All statistical analyses were performed with the rstatix package using R (version 4.0.2; R Foundation for Statistical Computing, Vienna, Austria) in the RStudio program (version 1.3; RStudio, Boston, MA).
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6

Statistical Analysis of Immunoreactivity

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Differences in the number of immunoreactive pixels per measured area and total distance traveled between groups were determined by unpaired t-test or one-way analysis of variance (ANOVA) followed by the Tukey’s multiple comparison test or two-way ANOVA with repeated measure (two-way RM ANOVA) using GraphPad Prism 6 (GraphPad Software Incorporation, San Diego, CA, USA). Sample sizes used in this study were justified by a power analysis using R-studio program (Rstudio, Boston, MA, USA). Data were expressed as the mean ± SEM for each group. A statistical significance was determined by p < 0.05.
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7

Randomized Clinical Trial Allocation

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Prior to commencement of the study, computer-based randomization was done using R studio program (RStudio, Inc, Boston, Massachusetts), version 1.1.456. A randomization list stratified by study site was generated by a statistician for both treatment arms. For allocation concealment, opaque envelopes were serially numbered and treatment arm allocation cards were inserted according to the list. The envelopes were sealed and the study nurse who was responsible for patient enrollment wrote the unique patient ID on top of the sealed envelope. This envelope was opened by the study clinician only, to determine the treatment arm allocation and for dispensing study drugs.
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8

ICU Patient Statistical Analysis

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No statistical sample size calculation was performed a priori, and sample size was equal to the number of patients admitted to the ICU during the study period. Quantitative variables are presented as medians and interquartile range (IQRs) and compared by use of the Mann-Whitney Wilcoxon rank-sum test. Categorical variables are expressed as the number of patients (percentage) and compared by means of the chi-square or Fisher tests. All statistical tests were two-tailed, and statistical significance was defined as P < 0.05. Statistical analyses were assessed by the R studio program (version 1.3.1056 for Windows).
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9

Varietal Grape Pomace Characterization

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Analyses of variance and Fisher’s least significant difference (LSD) test were performed using the Statgraphics Centurion XVIII software (Statgraphics Technologies, Inc., The Plains, VA, USA) to determine the differences between the varietal grape pomace extracts. Principal component analysis (PCA) was carried out to study the association between variables and to determine similarities or differences between the varietal grape pomace extracts, using the RStudio program (R-Studio Inc., Version 2023.06.0, Boston, MA, USA).
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10

IL-10 Polymorphisms and Cancer Risk

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Statistical analysis was performed with R software for windows and R studio program (www.rstudio.com), version 3.2.3. The characteristics of the study subjects were reported as mean for age, medians for IL-10 level, and relative frequencies for sex, tobacco and alcohol consumption, and histological type. The effect of IL-10 polymorphisms on IL-10 plasma levels, as well as HNC, NPC, and LC were evaluated by setting homozygous major allele genotype as reference; subsequent analyses were performed using one-way ANOVA. Chi-quare test was used in comparing categorical data and Fisher exact test for low number. Receiver operating characteristic (ROC) curve was used to determine sensitivity and specificity; P < 0.05 was considered statistically significant. Linkage disequilibrium and haplotype reconstruction were performed using Haploview 4.2 (www.broadinstitute.org) software and SNPstats (u299e), which also tested for departure from Hardy–Weinberg equilibrium (HWE).
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