Statistical Programming

Since 2011 I’ve been using SAS 9.x and later R 3.x/4.x for statistical programming. These two languages were used for different types of clients, so the actual tasks are spilt below in two groups. Adherence to client SOPs, good programming practice and industry guidelines is an absolute must for me.

SAS programming
  • CDISC SDTM and ADaM standards
  • Developing specs and programming of datasets
  • TFL shells developing and programming
  • Main and QC side activities
  • Extensive use of SAS/MACRO language
  • Good knowledge of SAS/GRAPH system
  • SAS/ODS system for different types of outputs
  • Statistical procedures: PROC GLM, LIFETEST, PHREG etc.
  • Developing of study-level complex macros
  • PK analysis
R programming
  • Sample size estimation and study simulation
  • Complete efficacy and safety analysis
  • PK analysis
  • Extensive use of tidyverse packages for data manipulation: magrittr, dplyr, tidyr, stringr, lubridate.
  • Plots and figures with ggplot2
  • Creating MS Word compatible outputs with ReporteRs and officer packages
  • Developing standard functions for cross-study programming

Additionally I use Python 3 and VBA for cumbersome or non-standard tasks, such as:

  • Comparison of RTF outputs from obsolete studies where datasets are not available.
  • Batch re-naming of files
  • Conversion of multiple RTF files into PDF


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