Science Research Weekly

By Mark R Williamson

A weekly overview of helpful scientific research topics and the successor of the podcast Statistics Weekly. Every week, I will cover 3 topic areas: Research Articles, Research Tools, and Research Fund... more

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FAQs about Science Research Weekly:

How many episodes does Science Research Weekly have?

The podcast currently has 181 episodes available.

Science Research Weekly episodes:

June 03, 2022Episode 10: Multiple Last Names and Growing a Backbone
In this episode, I chained together multiple scientific last names, found heaps of PLOS ONE journal articles, and learned how to grow a backbone in R using package ‘backbone’.
References:
Event History Regression with Pseudo-Observations: Computational Approaches and an Implementation in R

More on Multidimensional Scaling and Unfolding in R: smacof Version 2

A Practical Guide to the Numerical Implementation of Tensor Networks I: Contractions, Decompositions, and Gauge Freedom

Rank-polyserial correlation. Quest for a "missing" coefficient of correlation

Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package

backbone: An R package to extract network backbones

Evaluation of spatial Bayesian Empirical Likelihood models in analysis of small area data

Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare

The interplay between ranking and communities in networks

Random assignment of subjects to groups in SAS

Using formatted CLASS variables

Python 3.11.0b2 is now available

shadowr: Selenium plugin to manage multiple levels of shadow elements on web page

Difference Between Standard Deviation and Standard Error

Clopper-Pearson Exact Method

Applications of Python | Top 10 uses of Python for The Real World

15 Fun & Easy Excel Project Ideas To Sharpen Your Skills

2022-01 Vectorised Pattern Fills in R Graphics

April: “Top 40” New CRAN Packages

R Packages Download Stats
R-packages:
AHSurv: Flexible Parametric Accelerated Hazards Models

misPRIME: Partial Replacement Imputation Estimation for Missing Covariates

tracee: Easily Save Output and Trace it Back to Code

backbone: Extracts the Backbone from Graphs
...more
10min
May 27, 2022Episode 9: Boxes and Babies
In this episode I thought outside the Box-Pierce; fuzzed, sweated, and flustered my way through basic stats; encountered functions and AI for babies; and chronicled the R-package ‘chronicler’.
References:
NeuralSens: Sensitivity Analysis of Neural Networks

econet: An R Package for Parameter-Dependent Network Centrality Measures

Modified Quantile Regression For Modeling the Low Birth Rate

A Novel Correction for the Adjusted Box-Pierce Test

Comments on identifying causal relationships in nonlinear dynamical systems via empirical mode decomposition

Adaptive numerical simulations with Trixi.jl: A case study of Julia for scientific computing

The balanced bootstrap in SAS

Game-changer AI tool will save mothers and babies

D. Mayo & D. Hand: “Statistical significance and its critics: practicing damaging science, or damaging scientific practice?”

Fuzzy Clustering: Definition

How to Find the P value: Process and Calculations

The Difference Between an Odds Ratio and a Predicted Odds

‘Data analysis with tidyverse’ workshop

Think like a programmeR: the workshop

How to add labels at the end of each line in ggplot2?

Subsetting with multiple conditions in R

Hierarchical data visualization with Shiny and D3

chronicler: Add Logging to Functions
R-packages:
Rwclust: Random Walk Clustering on Weighted Graphs

ScaleSpikeSlab: Scalable Spike-and-Slab

webshot2: Take Screenshots of Web Pages

mverse: Tidy Multiverse Analysis Made Simple

chronicler: Adding Logging to Functions
...more
11min
May 18, 2022Episode 8: Shortened Blankets
In this episode, I got lost in among the statistical trees, flipped a Bernoulli trial coin, and wrapped myself up in package ‘ggblanket’.
References:
sensobol: An R Package to Compute Variance-Based Sensitivity Indices

The R Package stagedtrees for Structural Learning of Stratified Staged Trees

Wave Effects of the Fractional Shallow Water Equation and the Fractional Optical Fiber Equation

Two Domains of Meandering Spiral Waves in a Modified Barkley Model

Access for success: SAS Certification practice exams now offered for free

How to unroll frequency data

Sampling Methods: Different Types in Research

Bernoulli Trials: Definition, Examples

ANCOVA: Analysis of Covariance

Measures of Model Fit for Linear Regression Models

ggblanket: making beautiful ggplot2 visualisation simpler

Self-documenting {ggplot}s thanks to the power of monads!

Launch of R Screencasts

How to draw heatmap in r: Quick and Easy way
R packages:
DemographicTable: Creating Demographic Table

Linea: Linear Regression Interface

linelist : Tagging and Validating Epidemiological Data

NovelDistns: Computes PDF, CDF, Quantile, Random Numbers and Measures of Inference for 3 General Families of Distributions

semtree: Recursive Partitioning for Structural Equation Models

getwiki R: Wrapper for Wikipedia Data

simer: Data Simulation for Life Science and Breeding

ggblanket: Wrappers to Make Beautiful 'ggplot2' Visualization Simpler

dimensionalAnalysis: Dimensional Analysis
...more
9min
May 13, 2022Episode 7: Riding the Python Lightning
In this episode, I dived into non-normal distributions, went from rags to ridges, rode the Python Language Summit lightning, and looked at the ‘GenericML’ package.

References:
Covsim: An R package for Simulating Non-Normal Data for Structural Equation Models Using Copulas

Rags2ridges: A One-stop-L2-shop for Graphical Modeling of High-Dimensional Precision Matrices

Transmissibility in Interactive Nanocomposite Diffusion: The Nonlinear Double-Diffusion Model

Editorial: Modelling collective motion across scales

The Application of the Functional Variable Method for Solving the Loaded Nonlinear Evaluation Equations

The derivative of the determinant of a matrix

Python 3.11.0b1 is now available

The 2022 Python Language Summit: Upstreaming optimisations from Cinder

The 2022 Python Language Summit: Performance Improvements by the Faster CPython team

The 2022 Python Language Summit: Python in the browser

The 2022 Python Language Summit: A per-interpreter GIL

The 2022 Python Language Summit: Achieving immortality

Fiducial Inference: Fisher’s Great Failure

Beta Distribution: Uses, Parameters & Examples

Geometric Distribution: Uses, Calculator & Formula

Alignment cheatsheet

5 Key Data Visualization Principles Explained – Examples in R

Three packages that port the tidyverse to Python

How to embed a Shiny app into your blog posts

R packages:
biogeom: Biological Geometries

GenericML: Generic Machine Learning Inference

PMA2: Penalized Multivariate Analysis
...more
9min
May 06, 2022Episode 6: Mixes and Metabolomics
In this episode, I dig into the first articles of a new Journal of Statistical Software volume, try not to mix up package ‘nvmix’ with ‘nmix’, scratch my head over Navier-Stokes equations, and take the random R-package section in a metabolomics direction.
References:
Journal of Statistical Software Volume 102

Convolutional Neural Networks for Very Low-Dimensional LPV Approximations of Incompressible Navier-Stokes Equations

Simulate the null distribution for a hypothesis test

Nmix package - Bayesian inference about univariate Gaussian mixtures with an unknown number of components

What is Power in Statistics?

Member Training: Introduction to SPSS Software Tutorial

Announcing R/Medicine 2022!

New Workshops Series Kick-off

Little useless-useful R functions – Animating datasets

March: “Top 40” New CRAN Packages

An introduction to the metabolomicsR
R packages:
arthistory: Art History Textbook Data

nls2: Non-Linear Regression with Brute Force

metabolomicsR: Tools for Metabolomics Data

conductor: Create Tours in 'Shiny' Apps Using 'Shepherd.js'
...more
10min
April 29, 2022Episode 5: Stretching the Limits and Vigorous Calisthenics
In this episode, I stretch before vigorous calisthenics, give a thumbs up to O’Reilly coding books, get to the bottom of R vectorization, try not to panic during debugging, and showcase the R-package ‘fauxnaif’.
References:
A NSFD Discretization of Two-Dimensional Singularly Perturbed Semilinear Convection-Diffusion Problems

Misnomers regarding outliers and their usefulness in statistical modeling

On Bartlett's sphericity test for correlation

Two perspectives on numerical integration

R 4.2.0 Released

Parameter vs Statistic: Examples & Differences

Spurious Correlation: Definition, Examples & Detecting

Hey, check this out, it’s really cool: A Bayesian framework for interpreting findings from impact evaluations

Top 10 Best R Books For Beginners

How to create your own functions in R

RObservations #30: Fixing R’s “messy string concatenation” with a special function

Where for (loop) ARt Thou?

RStudio Community Table Gallery

Don’t Panic! a Scientific Approach to Debugging Production Failure

R packages:
CircularSilhouette:   Fast Silhouette on Circular or Linear Data Clusters

forplo:   Flexible Forest Plots

pspatreg:   Spatial and Spatio-Temporal Semiparametric Regression Models with Spatial   Lags

SLBDD:   Statistical Learning for Big Dependent Data

cleaR:   Clean the R Console and Environment

gameR:   Color Palettes Inspired by Video Games

prettymapr:   Scale Bar, North Arrow, and Pretty Margins in R

fauxnaif:   Convert Values to NA
...more
8min
April 22, 2022Episode 4: Stealing Python’s Thunder and Rolling Your Rs
In this episode, I jump into Julia packages, estimate how to pronounce the generalized Kibria-Lukman estimator, commiserate with Python, and showcase the R-package ‘rsconnect’.

References:
Generalized Kibria-Lukman Estimator: Method, Simulation, and Application

Trending Julia Packages

Use a heat map to visualize an ordinal response in longitudinal data

The McNemar test in SAS

Happy Birthday Neyman: What was Neyman opposing when he opposed the ‘Inferential’ Probabilists? Your weekend Phil Stat reading

How to Interpret Adjusted R-Squared and Predicted R-Squared in Regression Analysis

Three Principles of Experimental Designs

MLDataR – Real-world Datasets for Machine Learning Applications

Getting started with Python using R and reticulate

Text Analysis of Job Descriptions for Data Scientists, Data Engineers, Machine Learning Engineers and Data Analysts
R-packages:
bookdown: Authoring Books and Technical Documents with R Markdown

rconfig: Manage R Configuration at the Command Line

BayesPPD: Bayesian Power Prior Design

spatialreg: Spatial Regression Analysis

pagoda2: Single Cell Analysis and Differential Expression

microeco: Microbial Community Ecology Data Analysis

paletteknife: Create Colour Scales and Legend from Continuous or Categorical Vectors

starter: Starter Kit for New Projects

rsconnect: Deployment Interface for R Markdown Documents and Shiny Applications
...more
7min
April 15, 2022 Episode 3: Jackknifing, Leibniz, and Feeling the Python Breeze
In this episode, I play with jackknives, chuckle over Python, list upcoming R conferences, and showcase the R-package ‘RcppBDT’.

References:
Additive Noise-Induced System Evolution (ANISE)
Face Recognition in Single Sample Per Person Fusing Multi-Scale Features Extraction and Virtual Sample Generation Methods
An Epidemiological Compartmental Model With Automated Parameter Estimation and Forecasting of the Spread of COVID-19 With Analysis of Data From Germany and Brazil
Accelerating Jackknife Resampling for the Canonical Polyadic Decomposition
The last Python 3.11 alpha (3.11.0a7) is available
New methods for solving differential equations in SAS
Pascal matrices and inverses
Enhancements to HTML Documentation
Some discussion of “how to get confident with statistics”: Reading, practicing, and questioning
Permutation vs Combination: Differences & Examples
Chi-Square Goodness of Fit Test: Uses & Examples
SPSS Syntax 101
The sftime Package
To impute or not: the case of an RCT with baseline and follow-up measurements
Why you should(n’t) care about Monads if you’re an R programmer
Bayesian Estimation by using rjags Package
Upcoming R conferences (2022)

R-packages:
clusterHD: Tools for Clustering High-Dimensional Data
Allspice: RNA-Seq Profile Classifier
cheatR: Catch Cheaters
spooky: Time Feature Extrapolation Using Spectral Analysis and Jack-Knife Resampling
taxonbridge: Create Custom Taxonomies Based on the NCBI Taxonomy and GBIF Backbone Taxonomy
wrMisc: Analyze Experimental High-Throughput (Omics) Data
findInFiles: Find Pattern in Files
mclogit: Multinomial Logit Models, with or without Random Effects or Overdispersion
aRtsy: Generative Art with 'ggplot2'
glmm: Generalized Linear Mixed Models via Monte Carlo Likelihood Approximation
glmtoolbox: Set of Tools to Data Analysis using Genera
RcppBDT: 'Rcpp' Bindings for the Boost Date_Time Library
...more
9min
April 08, 2022 Episode 2: Lies, Two-Truths and a Lie, and Statistical R-packages
In this episode, I drink from the firehose of CRAN packages, learn a use for ‘two truths and a lie’ in the statistics classroom, and showcase the R-package ‘pipeliner’.

References:
https://www.frontiersin.org/articles/10.3389/fams.2022.848898/abstract
https://www.frontiersin.org/articles/10.3389/fams.2022.852314/full
https://stat.ethz.ch/pipermail/r-announce/2022/000681.html
https://cran.r-project.org/web/packages/available_packages_by_date.html
https://www.spss-tutorials.com/open-excel-file-in-spss/
https://www.spss-tutorials.com/spss-missing-values-for-string-variables/
https://errorstatistics.com/2022/04/05/insevere-tests-of-severe-testing/
https://statmodeling.stat.columbia.edu/2022/04/04/two-truths-and-a-lie-as-a-class-participation-activity/
https://statmodeling.stat.columbia.edu/2022/04/05/confidence-intervals-compatability-intervals-uncertainty-intervals/
https://www.statisticshowto.com/research-methods-qualitative-research-and-quantitative-research/
https://statisticsbyjim.com/basics/cohort-study/
https://statisticsbyjim.com/hypothesis-testing/sampling-error/
https://www.r-bloggers.com/2022/04/paper-semi-markov-modeling-for-cancer-insurance/
https://www.r-bloggers.com/2022/04/teaching-data-science-in-the-cloud/
https://www.r-bloggers.com/2022/04/new-features-in-r-4-2-0/
https://www.r-bloggers.com/2022/04/bio7-3-4-released/
https://cran.r-project.org/web/packages/pipeliner/index.html
https://cran.r-project.org/web/packages/pipeliner/vignettes/Introduction.html
...more
8min
April 01, 2022 Episode 1: Getting a Flat Distribution Under Us
In this episode, I brace myself for the R release of Vigorous Calisthenics, scratch my head at Lyapunov Exponents, survey the brewing battlefield in the AI/ML Wars, and showcase the R-package 'numform'.

References:
https://journal.r-project.org/archive/2021/RJ-2021-109/RJ-2021-109.pdf
https://journal.r-project.org/archive/2021/RJ-2021-080/RJ-2021-080.pdf
https://www.jstatsoft.org/article/view/v101i12
https://www.frontiersin.org/articles/10.3389/fams.2022.818799/full
https://www.frontiersin.org/articles/10.3389/fams.2022.869999/full
https://www.frontiersin.org/articles/10.3389/fams.2022.839669/full
https://cran.r-project.org/index.html
https://pythoninsider.blogspot.com/2022/03/python-3110a6-is-available.html
https://blog.python.org/2022/03/python-3103-3911-3813-and-3713-are-now.html
https://blog.python.org/2022/03/python-3104-and-3912-are-now-available.html
https://julialang.org/blog/2022/02/10years/
https://www.statistics.com/data-literacy-the-chainsaw-case/
https://errorstatistics.com/2022/03/23/the-ai-ml-wars-explain-or-test-black-box-models/
https://statmodeling.stat.columbia.edu/2022/03/27/the-examples-you-see-in-the-textbooks-are-not-representative-of-the-sorts-of-problems-you-see-in-the-real-world/
https://statisticsbyjim.com/regression/interpret-coefficients-p-values-regression/
https://www.r-bloggers.com/2022/03/february-2022-top-40-new-cran-packages/
https://www.r-bloggers.com/2022/03/how-i-analyze-100-ggplots-at-once/
https://cran.r-project.org/web/packages/numform/numform.pdf
...more
8min

FAQs about Science Research Weekly:

How many episodes does Science Research Weekly have?

The podcast currently has 181 episodes available.