22 citations · 36 across the 7 of their papers we have counts for
7 papers
A Journey from Wild to Textbook Data to Reproducibly Refresh the Wages Data from the National Longitudinal Survey of Youth Database
Dewi Amaliah, Dianne Cook, Emi Tanaka +2
Textbook data is essential for teaching statistics and data science methods because they are clean, allowing the instructor to focus on methodology. Ideally textbook data sets are…
brolgar: An R package to BRowse Over Longitudinal Data Graphically and Analytically in R
Nicholas J Tierney, Dianne Cook, Tania Prvan
Longitudinal (panel) data provide the opportunity to examine temporal patterns of individuals, because measurements are collected on the same person at different, and often irregul…
When to Impute? Imputation before and during cross-validation
Byron C. Jaeger, Nicholas J. Tierney, Noah R. Simon
Cross-validation (CV) is a technique used to estimate generalization error for prediction models. For pipeline modeling algorithms (i.e. modeling procedures with multiple steps), i…
A Realistic Guide to Making Data Available Alongside Code to Improve Reproducibility
Nicholas J Tierney, Karthik Ram
Data makes science possible. Sharing data improves visibility, and makes the research process transparent. This increases trust in the work, and allows for independent reproduction…
R-miss-tastic: a unified platform for missing values methods and workflows
Imke Mayer, Aude Sportisse, Julie Josse +2
Missing values are unavoidable when working with data. Their occurrence is exacerbated as more data from different sources become available. However, most statistical models and vi…
Expanding tidy data principles to facilitate missing data exploration, visualization and assessment of imputations
Nicholas J Tierney, Dianne H Cook
Despite the large body of research on missing value distributions and imputation, there is comparatively little literature with a focus on how to make it easy to handle, explore, a…
A Simple Guide to S3 Methods
Nicholas Tierney
Writing functions in R is an important skill for anyone using R. S3 methods allow for functions to be generalised across different classes and are easy to implement. Whilst many R…