The largest database of trusted experimental protocols

3 634 protocols using r software

1

Grape Flavonoid Analysis via PCA

Check if the same lab product or an alternative is used in the 5 most similar protocols
All analyses were carried out using Statistica 12 (Statsoft Inc., Tulsa, USA). Mixed-model repeated-measures (2010/2011 = 8; 2011/2012 = 10) analyses of variance (ANOVAs) were used and Fisher’s least significant difference (LSD) corrections were used for post hoc analyses. Significant differences were judged on a 95% significance level (p ≤ 0.05). Pearson’s correlation coefficients were used to construct heatmap.2 R function using R software (R Foundation for Statistical Computing, Vienna, Austria). The distribution of grape flavonoid datasets was analyzed with principal component analysis (PCA) using R software (R Foundation for Statistical Computing, Vienna, Austria).
+ Open protocol
+ Expand
2

Predicting Axillary Lymph Node Metastasis Using Multimodal Ultrasound

Check if the same lab product or an alternative is used in the 5 most similar protocols
Statistical analyses were performed using SPSS (version 25.0; IBM Corp.) and R software (version 4.1.3; The R Foundation). Continuous variables were compared using independent t-test. Categorical variables were compared using the χ2 or Fisher's exact test. The Cohen κ statistic was used to assess interobserver agreement. All clinicopathological factors and conventional US features potentially associated with ALNM (P<0.05 in univariate analysis) were used to construct a clinicopathological model and a conventional US model. A nomogram was formulated based on multimodal US variables by the results of multivariate logistic analysis. Calibration was assessed using the calibration curve with 1,000 bootstrap samples to decrease overfit bias. The predictive performances were compared with AUC. Additionally, net reclassification improvement (NRI) was applied to evaluate incremental value, and decision curve analysis (DCA) to investigate the clinical usefulness of the nomogram. The ‘rms’ package was used for nomogram and calibration curve construction, the ‘rmda’ package for DCA and the ‘nricens’ package was used for NRI calculation. All packages were performed from R software (version 4.1.3; The R Foundation). P<0.05 was considered to indicate a statistically significant difference.
+ Open protocol
+ Expand
3

HLA Allele Frequency Comparison

Check if the same lab product or an alternative is used in the 5 most similar protocols
The carrier frequencies of individual HLA alleles in patients and controls were compared based on the dominant model using the χ2-test (R software; R Foundation for Statistical Computing). HLA alleles and haplotypes with frequencies less than 1% in cases and controls were excluded from the association analysis. Fisher’s exact test (R software; R Foundation for Statistical Computing) was used when one or more observed counts was less than 5. Significance levels were corrected by Bonferroni correction for multiplicity of testing by the number of comparisons. A corrected P value of <0.05 was considered statistically significant.
+ Open protocol
+ Expand
4

Randomized Controlled Trial of UCHA

Check if the same lab product or an alternative is used in the 5 most similar protocols
Suitable participants, who agree to participate in this RCT, will be randomly assigned to a UCHA group or a placebo group at a 1:1 ratio. A total of 164 eligible participants each will be allocated to the UCHA and placebo groups. An internet-based research randomizer (IRR) developed by the contract research organization (CRO), the Institute of Safety and Effectiveness Evaluation for Korean Medicine (ISEE), will perform the assignment. A random order will be generated by the CRO's independent professional statistician using the R software (The R Foundation for Statistical Computing, Vienna, Austria) and stratified by the hospital using random block sizes of 2 and 4 based on the allocation code provided by the R software.
+ Open protocol
+ Expand
5

Descriptive Statistical Analysis of COVID-19 Data

Check if the same lab product or an alternative is used in the 5 most similar protocols
Because the patient cohort in our study was not derived from random selection, all statistics are deemed to be descriptive only. Statistical analysis was performed using R software, version 3.6.2 (R Foundation for Statistical Computing) and SAS software (version 9.4, SAS institute). Quantitative variables were expressed as means (normal) or medians (skewed), standard deviation (SD), and range. Qualitative variables are described as raw numbers and percentages.
Mean: Test Student.
Skewed: Wilcoxon Mann Whitney.
Dichotomized variables were compared by using the χ2 statistics.
Correlations between CT workflow, French department, and the COVID-19 epidemic markers were tested by a Pearson’s correlation tests. The two-sample t test was used to search associations between means and standard deviations in the French departments.
Following medical and biological statistics standards, we set the type 1 error at 0.05.
Statistical analysis was performed using R software, version 3.6.2 (R Foundation for Statistical Computing) and SAS software (version 9.4, SAS institute).
+ Open protocol
+ Expand
6

Statistical Analysis of Tumor Gene Expression

Check if the same lab product or an alternative is used in the 5 most similar protocols
The statistical software SPSS (Statistical Package for the Social Sciences, version 17.0), the GraphPad Prism 6 (version 6.01) and the R software (The R Foundation for Statistical Computing, 3.3.1 version) were used for the statistical analysis. The Student's t-test (two-tailed) was used for the analysis of the gene copy number variation and transcripts levels between the tumor and the normal samples (real-time qPCR and RT-qPCR results). Statistical associations amongst the clinicopathological parameters were performed using different tests; ANOVA test was performed for analyzing continuous variables with categorical variables and the Pearson’s correlation test to verify the presence of a correlation between continuous variables. When the samples did not present a Gaussian distribution, the values were transformed with the log function in order to normalize the values’ distribution. The correlogram was prepared with GraphPad Prism 6 (version 6.01) and R software (The R Foundation for Statistical Computing, 3.3.1 version). All values are expressed as mean ± SD (standard deviation). The exceptions are the data presented in the box-plot graphics that represents the median, quartiles, and extreme values within a category. In all statistical comparisons, p < 0.05 was established as representing significant difference.
+ Open protocol
+ Expand
7

Postoperative Pain and Opioid Consumption

Check if the same lab product or an alternative is used in the 5 most similar protocols
The VAS and NRS scores were strongly correlated [19 (link)], and pain scores were measured on the same scale (0-10) in all included studies. In addition, opioid consumption was converted into fentanyl equivalents (μg). Therefore, we calculated the mean differences (MDs) for continuous outcomes (postoperative pain scores or cumulative opioid consumption). We calculated the 95% CI for all estimates. A random-effect model was used for all trial results, because of the possibility of different effect sizes across the studies. To measure heterogeneity among the trials, Higgins’ I2, the heterogeneity statistic Cochrane’s Q, and the corresponding P values were calculated. We considered I2 > 50% as significant heterogeneity.
Sensitivity analysis was performed by leave-one-out analyses using meta and dmetar packages in R software (version 3.6.3, R Foundation for Statistical Computing, Austria).
Publication bias was not assessed in this meta-analysis, because the number of included studies was less than 10.
We used Review Manager (RevMan, version 5.3, The Cochrane Collaboration) and R software (version 3.6.3, R Foundation for Statistical Computing, Austria) for all analyses.
+ Open protocol
+ Expand
8

Implant Survival Rate and Bone Loss Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols
The statistical procedure was described in detail in a previous publication (Benic et al. 2009) (link). The estimation of the implant survival rate was based on Kaplan-Meier analysis and a group comparison was made using the log-rank test (R software; R Foundation, Vienna, Austria). Only the cases with both test and control implants were used for the following analysis. For continuous parameters, the data distributions were represented with boxplots and the data were reported by means, standard deviations (SD), medians, 95% confidence intervals (95% CI), and ranges (SPSS software; SPSS Inc., Chicago, IL, USA). The paired ttest was applied to detect differences between the test and the control implants. Results of tests with p-values ≤ 0.05 were considered statistically significant (R software; R Foundation, Vienna, Austria). To control for multiple testing, the Benjamini and Hochberg False Discovery Rate was applied. The power of the comparison between test and control implants had been computed for the patient cohort examined at the 5-year examination. It showed > 95% power for MBL interprox .
+ Open protocol
+ Expand
9

Analyzing Parasitic Prevalence in Iberian Lynx

Check if the same lab product or an alternative is used in the 5 most similar protocols
Parasite prevalence was calculated based on Bush et al. [52 (link)], as the percentage of hosts infected by that parasite species, using a binomial distribution with the function “binom.test” in R software (www.r-project.org), establishing confidence limits within 95% confidence intervals (CI). The intensity of the infection was estimated as the mean number of parasite eggs/oocysts per infected hosts [53 (link)], using the McMaster quantitative technique, with a sensitivity of 50 eggs per gram (EPG) of faeces [25 ]. The χ2-test was calculated using the function “chisq.test” in R software (www.r-project.org) to assess significant differences between parasitic prevalence found in the Iberian lynx and at least one mesocarnivore, for a p-value ≤ 0.05.
+ Open protocol
+ Expand
10

Preoperative Microbiome Analysis and Factors

Check if the same lab product or an alternative is used in the 5 most similar protocols
For the statistical analysis of the preoperative demographic data, SPSS version 25.0 (IBM, Armonk, NY, USA) was used with Fisher’s exact and the Mann-Whitney U-test. Analysis of α- and β-diversities was performed using QIIME (version 1.9.1) and R software (version 2.15.3). The LEfSe combines standard tests for statistical significance (Mann-Whitney U-test) with LDA. The threshold for the logarithmic LDA score for the discriminative features was 3.0. The Mann-Whitney U-test was used to compare data between groups using R software (version 2.15.3). Permutations (P<0.05) were used to select a set of environmental factors that had significant effects on microbial distribution. Statistical significance was set at P<0.05 which was two-sided. RDA and Spearman correlations were drawn using R (version 3.6.2). Benjamini-Hochberg correction was applied, where appropriate.
+ 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!