Articles by [email protected]

Calculate all the CVs of all the QC Levels of all the Methods of all the Instruments at all the Sites all at once … with Sunquest LIS and dplyr

February 4, 2020 | 0 Comments

Background As part of our lab accreditation requirements, we have to provide measurement uncertianty estimates for all tests at all hospital sites. As you might imagine, with thousands of testcodes in Sunquest LIS, getting all the coefficients of variation (CVs) represents a daunting task for the quality technologist to accomplish. ...
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Compare Tube Types with R – Repeated Measures ANOVA

August 21, 2017 | 0 Comments

Background Sometimes we might want to compare three or four tube types for a particular analyte on a group of patients or we might want to see if a particular analyte is stable over time in aliqioted samples. In these experiments are essentially doing the multivariable analogue of the paired ... [Read more...]

Conditional Formatting of a Table in R

November 7, 2016 | 0 Comments

Background There are a few ways to approach the problem of a conditionally formatted table in R. You can use the ReporteRs package's FlexTable() function, the formattable package, or the condformat package. These allow you to produce a conditionally formatted tables in HTML. You can also use xtable package and ... [Read more...]

Make Easy Heatmaps to Visualize your Turnaround Times

September 8, 2016 | 0 Comments

The Problem In two previous posts, I discussed visualizing your turnaround times (TATs). These posts are here and here. One other nice way to visualize your TAT is by means of a heatmap. In particular, we would like to look at the TAT for every hour of the week in ... [Read more...]

Make Bland Altman Plots with Marginal Histograms using ggExtra

August 29, 2016 | 0 Comments

The Problem As you know in Clinical Chemistry, we are not always writing a major paper but sometimes just preparing a short-report to answer a technical question that we've encounted at work. For shorter papers, journals often have more stringent rules about how many figures you can submit and even ... [Read more...]

A Shiny App for Passing Bablok and Deming Regression

August 15, 2016 | 0 Comments

Background Back in 2011 I was not aware of any tool in R for Passing Bablok (PB) regression, a form of robust regression described in a series of three papers in Clinical Chemistry and Laboratory Medicine (then J Clin Chem and Biochem) available here, here and here. For reasons that are ... [Read more...]

Count The Mondays in a Time Interval with Lubridate

November 25, 2015 | 0 Comments

Recently, while working on quantifying the inpatient workload volume of routine tests as a function of the day of the week, I needed to be able to count the number of Mondays, Tuesdays, etc in a time–interval so I could calculate the average volume for each weekday in a ... [Read more...]

Making Youden Plots in R

October 15, 2015 | 0 Comments

Background I was honoured by a site visit by Drs. Yeo-Min Yun and Junghan Song of the Korean Society for Clinical Chemistry a few weeks ago. As both professors are on the organizing committee of the Cherry Blossom Symposium for Lab Automation in Seoul in Spring 2016, their primary motivation for ...
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Deming and Passing Bablok Regression in R

September 14, 2015 | 0 Comments

Regression Methods In this post we will be discussing how to perform Passing Bablok and Deming regression in R. Those who work in Clinical Chemistry know that these two approaches are required by the journals in the field. The idiosyncratic affection for these two forms of regression appears to be ...
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NA NA NA NA, Hey Hey Hey, Goodbye

September 5, 2015 | 0 Comments

Removing NA’s from a Data Frame in R The Problem Suppose you are doing a method comparison for which some results are above or below the linear range of your assay(s). Generally, these will appear in your spreadsheet (gasp!) program as ( y) or, in the case of our ...
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A Closer Look at TAT Time Dependence

August 28, 2015 | 0 Comments

The Problem We want to have a closer look at the time–dependence of turn around times (TATs). In particular, we would like to see if there is a significant trend in TAT over time (improvement or deterioration) and we would like the data to inform us of slowdowns and ...
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