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R-Project 3.1 is an open-source software environment for statistical computing and graphics. It provides a wide range of statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and others.

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Lab products found in correlation

5 protocols using r project 3

1

Electrophysiological Analysis of Neuron Dynamics

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All bar graphs were shown as mean ± SEM. All statistical analyses were performed using Graphpad Prism (version 7) or R-Project3.1, and a p value of < 0.05 was considered significant. The specific n for each experiment as well as the post hoc test corrected p values, can be found in the Results section, in the Figure legends or in supplementary tables.
S = (s1, 1 s1,2 s1,… s1, N s2, 1 s2,2 s2,… s2, N s…,1 s…,2 s1,… s…,N s16, 1 s16, 2 s16,… s16, N), and d(·) is the first difference operator computed by column. For more theory see (Hodgkin and Huxley, 1952 (link)).
Numerical values are given as mean ± SEM unless stated otherwise. 6 Controls, 7 Mafb cKOs, 6 c-Maf cKOs and 3 cDKOs were used. For statistical analyses, we used parametric and nonparametric tests. We assessed statistical significance, as appropriate, by performing two-way ANOVA and the Kolmogoroff-Smirnoff test using R-Project 3.1.
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2

Electrophysiological Analysis of Neuron Dynamics

Check if the same lab product or an alternative is used in the 5 most similar protocols
All bar graphs were shown as mean ± SEM. All statistical analyses were performed using Graphpad Prism (version 7) or R-Project3.1, and a p value of < 0.05 was considered significant. The specific n for each experiment as well as the post hoc test corrected p values, can be found in the Results section, in the Figure legends or in supplementary tables.
S = (s1, 1 s1,2 s1,… s1, N s2, 1 s2,2 s2,… s2, N s…,1 s…,2 s1,… s…,N s16, 1 s16, 2 s16,… s16, N), and d(·) is the first difference operator computed by column. For more theory see (Hodgkin and Huxley, 1952 (link)).
Numerical values are given as mean ± SEM unless stated otherwise. 6 Controls, 7 Mafb cKOs, 6 c-Maf cKOs and 3 cDKOs were used. For statistical analyses, we used parametric and nonparametric tests. We assessed statistical significance, as appropriate, by performing two-way ANOVA and the Kolmogoroff-Smirnoff test using R-Project 3.1.
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3

Survival Analysis of Cancer Patients

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Continuous variables were described as median and interquartile range and were compared using the Mann–Whitney U test because of their abnormal distribution. Categorical variables were reported as numbers with percentages, and they were assessed using the chi‐square test or the Fisher exact test where appropriate. DFS and OS were calculated using the Kaplan–Meier method and performed through log‐rank test between group comparisons. Univariate survival analysis for OS and DFS was evaluated using a Cox proportional hazards model. The statistical analyses were performed through SPSS 22.0 and R‐project 3.5.1. A two‐sided p value <0.05 was regarded with statistical significance.
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4

Dosimetric Comparison of CMRO and PTV Plans

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The CMRO-plans were compared against the PTV-plans using dosimetric parameters of the EAGD of the CTVs and OARs. The investigated OARs reflected those used in our clinical practice. Target coverage conformity was defined by the conformity index (CI) [19] (link):
where 𝑉 intersect is the absolute volume of the CTV that received 95% of the prescribed dose and 𝑉 CTV is the volume of the CTV. Target homogeneity was defined as:
where D p is the prescribed dose to the target [3] (link). To derive the HI of the prophylactic CTV the primary CTV (+5.0 mm) was excluded from it. In addition, all plans were evaluated by NTCP values for xerostomia [20] , grade 2-4 dysphagia [20] , and tube feeding dependence [21] (link).
A paired Wilcoxon signed-rank test was used to calculate two-tailed p-values (R-Project 3.5.1, Vienna, Austria). The statistical significance was determined after accounting for multiple testing using Bonferroni's correction [22] . Differences were considered statistically significant if p < 0.005 (α = 0.05/10 structures) for OAR doses, p < 0.008 (α = 0.05/6 parameters) for target coverage and p < 0.017 (α = 0.05/3 NTCPs) for NTCPs.
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5

Multivariate Analysis of Therapeutic Impacts

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Statistical analysis was performed using R-Project 3.1 for GNU Linux Ubuntu (Vienna, Austria). For categorical variables, percentages were computed. Comparisons of percentages were performed with Fisher's exact test. We performed a multivariate analysis to assess the independent factors of therapeutic and diagnostic impact.
Variables with a significance level at least 0.1 were included in the logistic regression model. The variables were selected by a step-by-step forward-backward model to minimize the Akaike's criterion. The statistical threshold for final significance was 0.05.
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