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I was just notified by CRAN that choroplethr is scheduled to be archived on February 12. The reason is that choroplethr depends on the acs package, and the acs package is being archived. Apparently when a package is archived from CRAN, all packages which use it are also archived. I am not exactly sure what […]
When working with statistical data, ensuring that certain assumptions are met is critical to the validity of your results. One such assumption is the homogeneity of variance, which refers to the idea that the variability within groups should be consistent across all groups being compared. But how do you test this assumption effectively?Levene’s Test in R is a robust statistical test and is a go-to solution for researchers and data analysts who want to easily verify this assumption. This article’ll explore the what, why, and how of using the Levene Test in R, including step-by-step instructions and practical examples. Key Points The Levene Test is used to assess the homogeneity of variances across groups. Proper data preparation and assumption validation are crucial. R offers robust tools like leveneTest() in the car package for implementation. Visualization adds depth to variance analysis. Based on data characteristics, alternatives like Bartlett’s and Fligner-Killeen Tests should be considered. Statistical analysis often requires comparing data from different groups to determine if they follow similar patterns. One critical assumption in many tests, like ANOVA, is the homogeneity of variances. The Levene Test, a statistical procedure designed to test this assumption, ensures that group variances are equal before further analysis. Table of Contents Aspect Details Purpose Tests the null hypothesis that variances are equal across groups. Function in R leveneTest(response ~ group, data = dataset) Assumptions Independent observations Continuous dependent variable Categorical grouping variable Interpretation A p-value < 0.05 indicates significant differences in variances among groups. Alternative Tests Brown-Forsythe Test: More robust when data have heavy tails O'Brien's Test: Preferred for skewed distributions Case Studies Weight Loss Programs: Levene's Test identified unequal variances in weight loss across different programs. Sociology Exam Scores: Applied to determine variance equality between male and female students' scores. Understanding the Levene TestThe accuracy of statistical methods like ANOVA or regression hinges on equal variances across groups. Ignoring variance differences can lead to incorrect results, compromising the reliability of your conclusions. The Levene Test offers a robust way to validate this assumption, making it indispensable for researchers and students analyzing data in R programming or other statistical tools. What is the Levene Test? The Levene Test is a statistical method for assessing the equality of variances across two or more groups. It evaluates whether the variability in data is consistent across categories, which is a fundamental assumption in many parametric tests. The Levene Test determines whether groups exhibit similar variability by comparing deviations from the mean (or median).Read More »
Nuevo vídeo de R en Español sobre cómo Crear Funciones. Este vídeo es parte de mi playlist R Desde Ceros que pretende enseñar los aspectos mas básicos del uso de R para generar las bases para programación y análisis de datos. En este vídeo m...
I recently learned from Allen Downey’s blog that Our World in Data is providing API access to their data. Our World in Data hosts datasets across several important topics, from population and demographic change, poverty and economic development, to human … Continue reading →
The registration for the incoming, exciting, Bayes Comp 2025 conference (and its satellites) is now open, including information regarding accommodations for the conference. Early bird rates run till 15 March. Furthermore, the call for contributed talk...
Hey Shiny Enthusiasts! ShinyConf 2025 is just around the corner, and we’re thrilled to invite you to be a part of it! Whether you’ve been working with Shiny for years or just dipped your toes into the world of interactive web apps, this is your chance to share your journey, your innovations, and those lightbulb […] The post appeared first on appsilon.com/blog/.
Developing GxP-validated applications that comply with strict regulatory requirements has been a significant challenge in the past, particularly due to the lack of tooling around good software development practices. This is no longer the case, over the years, many tools have been developed to help R programmers follow good software development practices and write high-quality […] The post appeared first on appsilon.com/blog/.
I was recently discussing the analytic plan for a randomized controlled trial (RCT) with a clinical collaborator when she asked whether it’s appropriate to adjust for pre-specified baseline covariates. This question is so interesting because it touc...
Join our workshop on Decomposing within and between person effects in longitudinal data with SEM in R, which is a part of our workshops for Ukraine series! Here’s some more info: Title: Decomposing within and between person effects in longitudinal data with SEM in R Date: Thursday, February 27th, 18:00 – 20:00 CET (Rome, Berlin, … Continue reading Decomposing within and between person effects in longitudinal data with SEM in R workshopDecomposing within and between person effects in longitudinal data with SEM in R workshop was first posted on January 27, 2025 at 2:17 pm.
About From cpp11 description: “Provides a header only, C++11 interface to R’s C interface. Compared to other approaches ‘cpp11’ strives to be safe against long jumps from the C API as well as C++ exceptions, conform to normal R function semantic...
This week we had a wonderful community call, From Novice to Contributor: Making and Supporting First-Time Contributions to FOSS, where Sunny Tseng, Pascal Burkhard, and Yaoxiang Li shared with us their experiences with, and advice for, first time cont...
The variance-covariance and the correlation matrices are two entities that describe the association between the columns of a two-way data matrix. They are very much used, e.g., in agriculture, biology and ecology and they can be easily calculated wi...
This week we had a wonderful community call, From Novice to Contributor: Making and Supporting First-Time Contributions to FOSS, where Sunny Tseng, Pascal Burkhard, and Yaoxiang Li shared with us their experiences with, and advice for, first time cont...
I sometimes use this fun interview question for aspiring data scientists: How are p-values distributed assuming the null hypothesis is true? I’ve heard a lot of reasonable answers, including: All very reasonable and intuitive answers which I would probably, at some point, have given myself. They’re also all wrong. The (perhaps surprising) answer is that […] The post How Are P-values Distributed Under The Null? first appeared on David's blog.
My final exam for the Monte Carlo course I taught last semester proved too much of a challenge for my fourth year students, despite being rather elementary and centred on accept-reject algorithms and importance/bridge sampling. One of the problems was a decomposition of the truncated Normal simulation method proposed by Marsaglia in 1963, found on […]
Introduction In the dynamic world of clinical research, innovation and collaboration are key drivers of success. The NEST and ADaM in R Asset Library • admiral {admiral} teams exemplify this through their groundbreaking packages. By levera...
How can we teach “R for cell biologists” rather than teaching R to cell biologists? I’ve noticed that many R training courses will teach R – regardless of who is taking the course – and leave it to the participants to figure out how they can use R in their own discipline. Often, folks from […]
Join our workshop on Tabular ML in R: an overview of tidymodels in R for tabularized data, which is a part of our workshops for Ukraine series! Here’s some more info: Title: Tabular ML in R: an overview of tidymodels in R for tabularized data Date: Thursday, February 20th, 18:00 – 20:00 CET (Rome, Berlin, … Continue reading Tabular ML in R: an overview of tidymodels in R for tabularized data workshopTabular ML in R: an overview of tidymodels in R for tabularized data workshop was first posted on January 20, 2025 at 4:08 pm.
Extensive benchmark based on 1311 time series from the Tourism competition, comparing the splitconformal method to the state of the art.
Maintaining Community Trust and Safety The rOpenSci community is supported by our Code of Conduct with a clear description of unacceptable behaviors, instructions on how to make a report, and information on how reports are handled. We, the Code of Co...
How to join this free online event with Yi-Chin Sunny Tseng, Pascal Burkhard, Yaoxiang Li and Hugo Gruson. Contributing to open source can be very rewarding, but also incredibly intimidating. When we asked about first time contributions on the rOpenSc...
Introduction Like alot of lecturers I’m teaching at the moment. If I have a presentation to do that’s mainly images I’ll use Powerpoint or Google Slides. If the presentation includes maths or code or both I used to use LaTeX Beamer. Over the years ...