Add beautifully aligned text to paths and lines in your ggplot2 visualizations with geomtextpath, an extension that allows you to embed text directly onto plot lines in R. This package lets you add labels that follow the curvature of lines, making it easier to annotate plots while maintaining readability and style.
Key advantages of geomtextpath include:
✔️ Clear Annotations: Place text along lines for clear, context-specific labeling, reducing the need for separate legends or labels.
✔️ Enhanced Readability: Text follows the line's curvature, ensuring it stays aligned with the visual flow of the plot.
✔️ Flexible Customization: Adjust font, position, angle, and style to match your design needs and maintain a cohesive look.
To use geomtextpath in ggplot2, replace standard line geoms with geom_textpath() or geom_labelpath() and specify your text as an aesthetic. This simple addition allows you to embed text smoothly along plot lines, making it ideal for line graphs, contour plots, and other curved paths.
The example visualization shown here is from the geomtextpath package website and demonstrates these text-on-path capabilities: https://t.co/eul3wLXi5F
If you’re interested in mastering text and annotation techniques in R, consider joining my course, "Data Visualization in R Using ggplot2 & Friends!"
Learn more by visiting this link: https://t.co/ztlEzoEDWv
#RStats #ggplot2 #DataViz #VisualAnalytics #statisticsclass #RStudio
Honored to present BREATHS trial in progress at #ASCO25! -first to investigate whether in-bedroom air filtration, when added to standard of care, improves systemic inflammation and cardiac biomarkers in cancer survivors with high risk of cardiovascular toxicity.
Grateful to Prof Andrew Edkins, @e_chrysikou, @JMOM85, @DrN_CancerPCP, @_jbk, Prof Gary McLean, Hannah Frost; and @UCL_BSSC for supporting me to attend @ASCO.
Thank you @IQAir, @premalabs & LansionBio, & @AND_Medical for the equipment support provided for the trial.
| Journal of Clinical Oncology https://t.co/ogTaM7SInm
Despite our best efforts, without more robust built in evaluation, it is hard to know how effective lock downs and other non-pharmacological interventions were in the pandemic. See https://t.co/cZRsaUdGdH A pleasure to work with colleagues on this project.
Our paper is open access and has been published by the Journal of Public Health.
With thanks to our colleagues from the Usher Institute, UNCOVER | Applied Evidence Synthesis, University of Edinburgh https://t.co/SdbG8fa6AD who led the work with help from https://t.co/tr9ZizQmXw
One of the largest and most heterogeneous systematic reviews I have ever worked on:
https://t.co/xf3aLMivw7
We aimed to examine the effectiveness of non-pharmacological interventions implemented in the UK during the COVID-19 pandemic...
These studies and interventions were implemented quickly during the pandemic, when they were most needed. However, to support future pandemic and public health emergencies decision-making, we need to improve the process of rapid high-quality evidence generation and evaluation.
Unlocking the full potential of your linear regression analysis starts with validating its suitability. Here’s a summary of how to validate assumptions before applying this model:
1️⃣ Linearity: The relationship between predictors (independent variables) and the response (dependent variable) should be linear. Think of a car traveling at a constant speed: the distance traveled increases proportionally with time.
2️⃣ Independence: Residuals (errors) must be independent of each other. Picture students taking an exam in separate rooms without communication. Each student's score is independent of the others.
3️⃣ Homoscedasticity vs. Heteroscedasticity: Residuals should have a constant spread across all levels of the independent variable. If the variability changes, like scores varying differently for easy versus hard exam questions, it indicates heteroscedasticity, which is problematic.
4️⃣ Normality of Residuals (Multivariate Normality): Residuals should follow a normal distribution, similar to the bell curve seen when rolling a fair die many times.
5️⃣ No Multicollinearity: Independent variables should not be highly correlated with each other. Imagine assessing the impact of both age and experience on salary: if they move together, it’s hard to distinguish their individual effects.
6️⃣ Measurement Error: Measurement errors can lead to unreliable predictions. It’s like weighing fruits on a scale that occasionally gives wrong readings.
The visualization originates from a recent post by @intelligentle__
#statistics #regression #statisticalmodeling #datascience
@dnunan79 I remember when I was competing in swimming (many years ago) we also used that but only to prepare a home-made isotonic beverage (we were also adding to water a bit of salt, sugar, and lemon juice) I don't think it'd enhance the performance beyond any other isotonic beverage
Looking forward to the lecture: Meta-analysis of individual participant data in vaccine research by Associate Professor @MerrynVoysey at Rewley House on Thursday 20 June 2024, 17:30-18:30. If you'd like to attend, register here:
https://t.co/HrGStcxuHx
Wow, this response! 😮 We really do have complex jobs, huh? My doctoral research was on burnout, & I won't say that is UNRELATED to the graphic either.
Here's a slightly updated version. And as per requests, link to a PPT version you can download & adapt https://t.co/8v8jPhObx5
Nice to see this review published https://t.co/Q3Ao3Dt2ic It illustrates the need for more real world evidence studies to compliment studies in CKD run on some higher risk patient groups. @clininf@OxPrimaryCare
Check out our latest paper on the generalisability of #kidney trials populations receiving #SGLT2 inhibitors
Less than 10% of UK primary care population with #CKD would be eligible for these trials
@OxPrimaryCare@ORCHID_Oxford@lusignan_s
https://t.co/c7ExSg6Gvt
In Seville, at this time of the year, the Town Hall leaves the picked oranges under the fruit trees placed in the streets for both locals and visitors to enjoy.
Credits: @ErPali_
How has the COVID-19 pandemic affected the delivery of preventive healthcare?
"Advice and support for smoking, and advice for weight, excess alcohol and physical inactivity have not returned to pre-pandemic levels."
https://t.co/MKeoGaXCOw
@OxPrimaryCare@ORCHID_Oxford