Issue R files shown as 0 KB. R files reopened as empty in RStudio.Solution I had a similar issue with older R files that opened as empty. It turned out that RStudio didn’t use the correct encoding as default and therefore wasn’t able to read the file (presented the file as empty). You can make sure that you are using the correct encoding by:0. Copying R code to a text file

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ERROR An error occurred executing the workspace job “autoexec”. SDS Failed to provide the SAS workspace. SAS.EC.Directory.Model.SDSEXception

An interim analysis (IA) is conducted before data collection has been completed. Clinical trials are unusual in that enrollment of subjects is a continual process staggered in time. If a treatment can be proven to be clearly beneficial or harmful compared to the concurrent control, or to be obviously futile, based on a pre-defined analysis of an incomplete data set while the study is on-going, the investigators may stop the study early.

The code above produces this plot

Resize 1 photo # Bring installed packages to memory library(jpeg) library(dplyr) library(foreach) library(doParallel) # Input and output directories dir.C.drive <-"C:" dir.G.drive <- "G:/My Drive"

R code used to generate outcome demonstrated during knowledge hour presentation at GLC 21-04-2023 Set up directory # Input and output directories dir.C.drive <-"C:" dir.R.packages <- file.path(dir.C.drive,"R","R-4.1.3") dir.main <- file.path(dir.C.drive,"Google-Drive") dir.GLC <- file.path(dir.main,"Greenlight-clinical") dir.GLC.presentation <- file.path(dir.GLC,"Knowledge-hours-presentation") dir.GLC.data <- file.path(dir.GLC.presentation, "data-download")

What is Pinnacle 21? Pinnacle 21, also known as OpenCDISC Validator, provides great compliance checks against CDISC outputs like SDTM, ADaM, SEND and Define.xml.Common Pinnacle 21 Report Issues: Shall we Document or Fix? Pinnacle 21 validation report PINNACLE 21 COMMUNITY VALIDATOR TOOL: Pinnacle 21 Community Validator is the leading industry tool for validating SDTM data sets against CDISC standards (for more information about CDISC standards, please see cdisc.org). After the validator has finished checking the SDTM data sets, findings are made available to the user, typically in Excel format. The findings report consists of four tabs: Datasets Summary, Issue Summary, Details, and Rules. The Datasets Summary tab provides an overview of the contents for each input file and contains summary information about the total number of records, errors, warnings, and notices for each domain. The Issue Summary tab breaks down issues by severity (error, warning, and notice) and by type for each domain. Each issue type is categorized by FDA Publisher ID, which represents the FDA’s published business rules. A description of each rule can be found on the Rules tab. The Details tab includes all issues in an expanded format and is presented on the record level. This tab includes the domain, record number, count, variables, values, rule ID, message, category, and severity for each issue.

The following code sorts data by placing 10, 11,…19 after 1 and then 2. That is because the sortkey IDVARVAL is character and SAS sorts data textually.

Using the R function in next section to get cut points for continuous predicting variables (predictors), dichotomise the predictors and run univariable cox regression Download a survival data file from QIMR L drive L:/Lab_MarkS/lunC/work/Immunohistochemistry_images/data_output/AP_Exp108.1_PeterMac-lungCancer-CD8-PD1/analysis-results/PeterMac-lung-cancer-cohort-1-DFS-marker-counts.tsv Create a new R script file. Copy the code chunk and modify the path of input, output files or folders Run the source() function to load the R function to the working environment. Modify the file path within the double quotes. Make sure backword slashes \ are replaced by forward slashes / when the path is copied from Windows address bar.

The aim is to scrape all the tables at Connect Chrome driver, RSelenium Data Analysis and Extraction - RSelenium tutorial Install R packages dir.R.packages <- "C:/Program Files/R/R-4.0.3/library" #install.packages("tidyquant", lib = dir.R.packages)

Author: Lun-Hsien Chang Date created: May 2020 Using the R function in next section to annotate all IHC images Download the cell segmentation data file cell-seg-data-merged_CD8.txt from QIMR L drive L:/Lab_MarkS/lunC/work/Immunohistochemistry_images/data_output/AP_Exp108.1_PeterMac-lungCancer-CD8-PD1/analysis-results Download the folder with IHC image files from QIMR L drive L:/Lab_MarkS/lunC/work/Immunohistochemistry_images/data_input/AshR/1. mIHF/Exp 108 210728/CD8 path Create a new R script file. Copy the code chunk below and modify the path of input files and folders. Run the source() function to load the R function to the working environment.