ggdag - Analyze and Create Elegant Directed Acyclic Graphs

Tidy, analyze, and plot directed acyclic graphs (DAGs). 'ggdag' is built on top of 'dagitty', an R package that uses the 'DAGitty' web tool (<https://dagitty.net/>) for creating and analyzing DAGs. 'ggdag' makes it easy to tidy and plot 'dagitty' objects using 'ggplot2' and 'ggraph', as well as common analytic and graphical functions, such as determining adjustment sets and node relationships.

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causal-inferencedagggplot-extension

13.11 score 464 stars 10 dependents 2.7k scripts 9.7k downloads

ymlthis - Write 'YAML' for 'R Markdown', 'bookdown', 'blogdown', and More

Write 'YAML' front matter for R Markdown and related documents. Work with 'YAML' objects more naturally and write the resulting 'YAML' to your clipboard or to 'YAML' files related to your project.

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9.88 score 168 stars 13 dependents 193 scripts 950 downloads

ggokabeito - 'Okabe-Ito' Scales for 'ggplot2' and 'ggraph'

Discrete scales for the colorblind-friendly 'Okabe-Ito' palette, including 'color', 'fill', and 'edge_colour'. 'ggokabeito' provides 'ggplot2' and 'ggraph' scales to easily use the 'Okabe-Ito' palette in your data visualizations.

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8.43 score 53 stars 9 dependents 424 scripts 8.8k downloads

propensity - A Toolkit for Calculating and Working with Propensity Scores

Calculates propensity score weights for multiple causal 'estimands' across binary, continuous, and categorical exposures. Provides methods for handling extreme propensity scores through trimming, truncation, and calibration. Includes inverse probability weighted estimators that correctly account for propensity score estimation uncertainty.

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7.57 score 23 stars 1 dependents 97 scripts 347 downloads

partition - Agglomerative Partitioning Framework for Dimension Reduction

A fast and flexible framework for agglomerative partitioning. 'partition' uses an approach called Direct-Measure-Reduce to create new variables that maintain the user-specified minimum level of information. Each reduced variable is also interpretable: the original variables map to one and only one variable in the reduced data set. 'partition' is flexible, as well: how variables are selected to reduce, how information loss is measured, and the way data is reduced can all be customized. 'partition' is based on the Partition framework discussed in Millstein et al. (2020) <doi:10.1093/bioinformatics/btz661>.

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data-reductiondimensionality-reductionpartitional-clusteringopenblascpp

7.29 score 37 stars 1 dependents 29 scripts 216 downloads

halfmoon - Techniques to Build Better Balance

Build better balance in causal inference models. 'halfmoon' helps you assess propensity score models for balance between groups using metrics like standardized mean differences and visualization techniques like mirrored histograms. 'halfmoon' supports both weighting and matching techniques.

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6.15 score 22 stars 91 scripts 684 downloads

precisely - Estimate Sample Size Based on Precision Rather than Power

Estimate sample size based on precision rather than power. 'precisely' is a study planning tool to calculate sample size based on precision. Power calculations are focused on whether or not an estimate will be statistically significant; calculations of precision are based on the same principles as power calculation but turn the focus to the width of the confidence interval. 'precisely' is based on the work of 'Rothman and Greenland' (2018).

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5.95 score 93 stars 19 scripts 214 downloads

metaconfoundr - Visualize 'Confounder' Control in Meta-Analyses

Visualize 'confounder' control in meta-analysis. 'metaconfoundr' is an approach to evaluating bias in studies used in meta-analyses based on the causal inference framework. Study groups create a causal diagram displaying their assumptions about the scientific question. From this, they develop a list of important 'confounders'. Then, they evaluate whether studies controlled for these variables well. 'metaconfoundr' is a toolkit to facilitate this process and visualize the results as heat maps, traffic light plots, and more.

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5.04 score 11 stars 9 scripts 275 downloads

tidysmd - Tidy Standardized Mean Differences

Tidy standardized mean differences ('SMDs'). 'tidysmd' uses the 'smd' package to calculate standardized mean differences for variables in a data frame, returning the results in a tidy format.

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4.89 score 9 stars 1 dependents 19 scripts 649 downloads

emptyfield - Install Empty Field Learning Materials

Install learning materials from Empty Field Data Science.

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2.65 score 1 stars 3 dependents 1 scripts

quarto.workshop - Install Materials for Reproducible Research in R with Quarto

Install learning materials for Reproducible Research in R with Quarto.

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quarto

2.30 score 4 stars

shunyata - Deploy Empty Field Teaching Material

This package helps set up new teaching material and deploy courses based on the Empty Field teaching workflow.

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quarto

2.00 score 1 stars 2 scripts

rrr.workshop - Install Materials for Reproducible Research in R

Install learning materials for Reproducible Research in R.

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1.70 score 1 scripts

rpkg.workshop - Install Materials for Developing R Packages

Install learning materials for Developing R Packages.

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1.70 score 1 scripts

opensky - Templates for 'ggplot2' and 'R Markdown'

Templates for 'ggplot2' and 'R Markdown'. 'opensky' provides functions to include templates for 'xaringan' slides, 'ggplot2' helpers, and 'R Markdown' documents.

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1.70 score 1 stars 3 scripts