Using R for Introductory Statistics

Verzani, John

doi:10.1201/9781315373089

Cited by 51 publications

(52 citation statements)

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“…Linear regression, analysis of variance (ANOVA) and Pearson product-moment correlations were performed in R (v2.13.1; R Development Core Team, 2011). Prior to statistical testing, data were evaluated for compliance with relevant assumptions and transformed appropriately when necessary (Verzani, 2005). The effect size of treatments was estimated using the omega squared (u 2 ) statistic according to Lakens (2013).…”

Section: Discussionmentioning

confidence: 99%

Sporocarp δ15N and use of inorganic and organic nitrogen in vitro differ among host-specific suilloid fungi associated with high elevation five-needle pines

2018

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Section: Discussionmentioning

confidence: 99%

Sporocarp δ15N and use of inorganic and organic nitrogen in vitro differ among host-specific suilloid fungi associated with high elevation five-needle pines

2018

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“…with all possible interactions among the three variables [20]. In order to investigate whethers-PCA3 could predict the Grade Group, a logistic model was applied [21]. All statistical analyses were performed with the R software [22].…”

Section: Discussionmentioning

confidence: 99%

A Low Score in Patients with a Positive PCA3 Urine Test Predicts the Lowest Prognostic Category in the New Grading System for Prostate Carcinoma

Rodón¹

2018

OAJCO

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Purpose: In this study we evaluate the PCA3 as a tool to improve prostate cancer (PCa) screening and it's capability to predict PCa aggressiveness. Materials and Methods:This retrospective study included data from consecutive patients with suspected PCa who presented to the urology office between November 2009 and April 2016 and were candidates for prostate biopsy. A total of 1038 urine samples were tested in our laboratory with a kit that generated a PCA3 score (s-PCA3). A prostate biopsy was recommended only in those patients with s-PCA3 ≥ 35. Associations between variables were analyzed using the R software. Results:In patients with a positive s-PCA3 (44.5%), a subsequent biopsy was recommended. A total of 151 biopsies were studied, 56.3% yielded a diagnosis of PCa. The probability of a positive biopsy increased as the s-PCA3 increased (p=0.041). The percentage of affected cylinders increased as the s-PCA3 increased (p=0.015). A statistically significant relationship was observed between s-PCA3 and both the Gleason score and the Grade Group (p=0.001 and 0.008, respectively). The best log linear models and a logistic model confirmed the relationships shown previously with Fisher's exact tests.Conclusions: s-PCA3 may serve as an additional marker to reduce the indication for biopsies and avoid overdiagnosis and overtreatment of patients with suspected PCa. The prognostic significance of s-PCA3 was confirmed, as it was associated with tumor volume and Gleason score. Importantly, to our knowledge this is the first time that an association has been demonstrated between s-PCA3 and the new Grade Group.

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“…It is not unusual to see quantile plots explained with the help of showing distributions along the axes (e.g., the cover and Figure 3.4 of Verzani, 2005), but to my knowledge authors have not exploited the water-filling analogy and resulting animation.…”

Section: Discussionmentioning

confidence: 99%

Explaining Normal Quantile-Quantile Plots Through Animation: The Water-Filling Analogy

Stine

2017

The American Statistician

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A normal quantile-quantile (QQ) plot is an important diagnostic for checking the assumption of normality. Though useful, these plots confuse students in my introductory statistics classes. A water-filling analogy, however, intuitively conveys the underlying concept. This analogy characterizes a QQ plot as a parametric plot of the water levels in two gradually filling vases. Each vase takes its shape from a probability distribution or sample. If the vases share a common shape, then the water levels match throughout the filling, and the QQ plot traces a diagonal line. An R package qqvases provides an interactive animation of this process and is suitable for classroom use.

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Using R for Introductory Statistics

Cited by 51 publications

References 0 publications

Sporocarp δ15N and use of inorganic and organic nitrogen in vitro differ among host-specific suilloid fungi associated with high elevation five-needle pines

Sporocarp δ15N and use of inorganic and organic nitrogen in vitro differ among host-specific suilloid fungi associated with high elevation five-needle pines

A Low Score in Patients with a Positive PCA3 Urine Test Predicts the Lowest Prognostic Category in the New Grading System for Prostate Carcinoma

Explaining Normal Quantile-Quantile Plots Through Animation: The Water-Filling Analogy

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