Back of the envelope analytics.
Assortment of posts regarding R programming, hardware design, statistics and other similar topics.
Thank God for people like Ben Lambert. I recently got acquainted with the BatchGetSymbols package, an auxiliary library to quantmod, and I am pretty impressed. It’s core function wraps a quality control protocol around quantmod’s getSymbols() function and returns a list with an execution summary and a daily price data datafame. This is a huge … Continue reading Scanning Stock Data for Co-integration Trade Opportunities
Alternative Title: How to kill 6 days during Spring Break. The unmasking of the opioids epidemic over the last several years has brought new scrutiny to marketing practices associated with high-risk pharmaceuticals products; Exposé journalistic efforts have been especially effective in shedding light on how misinformation and miscalculations of associated risk factors catalysed a torrent … Continue reading DEEP DIVE: Opioids ~ Unsupervised Methods for Kick-back Detection
Here’s a simple question: Why don’t watchlist screening vendors deploy semantic role labeling (SRL) methodologies when screening free-text fields? The value proposition is obvious — analysts would save hours of work each week by not having to clear false-positive alerts like the match of the word “shipped” to “XHAFERI, Shefit” (SDN). But seriously, this is … Continue reading SRL NPL for Sanctions Compliance
Sorry – no visualizations; Just a quick preview of things I’m hoping to roll out in the next month. I am going to try to do something a little unorthodox: use Rstudio’s Shiny framework to launch data exploration app (ahem!). …Sure, people use Shiny to build dashboards all the time, but the I don’t see … Continue reading Open Payments Data #4: Things to come.
First, some context: The requirement for direct-to-doctor (D2D) marketing transparency was enacted by Physician Payment Sunshine Act as part of ACA reforms in 2010. The call for transparency was initiated in response to concerns that D2D marketing practices by pharmaceutical & medical device companies may exert on undue influence on physician prescription practices. These concerns … Continue reading OpenPayments Data #3: Subsidiary Filings Prt. 2
One the my biggest data-quality frustrations with CMS data is the non-standardization of key fields, which prevents effective aggregation and analysis. The best example of this is the “payer” and “filer” fields. The payor fields Applicable_Manufacturer_or_Applicable_GPO_Making_Payment_ID and Applicable_Manufacturer_or_Applicable_GPO_Making_Payment_Name identify into the pharmaceutical companies making the payments. Although the ‘ID’ field is standardized for the most … Continue reading OpenPayments Data #2: Subsidiary Filings Prt. 1
I’m finally getting to a point where I can start exploring CMS Open Payments data after a couple months of on-and-off tying in complementary datasets. Spoiler: There’s probably going to be a decent amount of posts following this one on pharmaceutical marketing practices. I’m starting things off with a series of visualizations of how payments … Continue reading OpenPayments Data #1: Activity Distributions
ALAS! Why is gov’t data so terribly structured?! I’ve been working with the CMS Open Payments data recently because the annual datasets offer enough granular info to allow for good modeling practices and pharmaceutical marketing practices are pretty interesting from a policy stand-point. My only harp with the data is it’s poor data structure and … Continue reading rbindlist() for all of you list-of-dataframe monsters
The day was pretty stale seven hours ago – I was wrapped up some data project work and was studying for an upcoming exam when the news of Chester Bennington’s death broke. It ripped social media networks out of their midday slumber in a startling fit and began to reverberate across the internet. His death … Continue reading How We Write About Death and What We Remember
Too many the implemented models out there: On a serious note, I don’t ever want to hear the saying “garbage in, garbage out” ever again — but alas, I have no intentions of hunkering down in cave until the end of time. This proverbial phrase is thrown around so frequently in compliance circles that we … Continue reading Address Data Matching Methods for Sanctions Compliance
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