Month: January 2020

SAS: Tagset.Excelxp title and footnote setup

A. Multiple Titles/Footnotes

title
title2
title3
footnote
footnote2
footnote3

B. Alignment: default is center. 

justify=

C. Font

f=

D.Bold/Italic

bold italic

E. Font size

h=

F. Example

title1 f='Calibri' h=14pt 'Report Title';
title2 "Report Title1";
title3 "Report Title2";
footnote "Prepared by First Last on %sysfunc(date(),worddate.)";
footnote2 justify=left h=8pt bold "Note:";
footnote3 justify=left h=8pt italic "footnote3";

SAS: Date Functions and Date Value

A. Extract Month, Year information from DateTime.

  • Convert DateTime to Date using Datepart() first.
  • Use Year() and Month() function to get the Month and Year information
date=datepart(datetime);
year=year(date);
month=month(date);

B. Date Value for Date Comparison

  • ’17OCT1991’D is 11612, and is SAS date Oct. 17, 1991
  • use single quotation and D at the end
  • the day, month, or year in the date string can be replaced by macro variable to become dynamic. eg. ’01JUL&yr.” can be used for comparison of July 1 of different year.

C. Age calculation

  • Reference: https://communities.sas.com/t5/SAS-Enterprise-Guide/How-to-calculate-age-from-Date-of-birth-and-date-of-last-visit/td-p/572236
  • Reference: https://blogs.sas.com/content/iml/2017/05/15/intck-intnx-intervals-sas.html
  • intck function results whole year and yrdif function results decimal year.
  • In intck function, using the ‘continuous’ or ‘c’ option to return the number of full years. 
    age = intck('Year', birth, "01JUL&yr."D, 'C');

    SAS: Standard Errors

    A. Different Standard Errors

    • Standard Error of the Regression Model: (denote by s) usually referred to as the standard error of the regression or “standard error of the estimate”.
    • STDI: Standard Error of the individual predicted value (y_hat)
    • STDP: Standard Error of the mean predicated value
    • STDR:Standard Error of the residual
    • STUDENT: Studentized residuals, the residual divided by its standard error

    B. Estimate function in the GLM procedure

    R: RStudio Plots not showing in the Plots Window

    A. Symptom

    The plots stopped showing in the pane when running the R codes. The temporary png file generated in the folder didn’t have the graphic output and the file was not able to be deleted.

    B. R Code Caused problem

    png(file='Construct.png') 
subgroup.analysis.mixed.effects(x = m.hksj, subgroups = madata$Construct, plot=TRUE)
dev.off

    In R use png(file=) and dev.off to generate graphic output in the working directory. The subgroup.analysis.mixed.effect function doesn’t work with this method, hence the output graphic file got stuck.

    C. Fix

    dev.cur()   # to identify output device as "png 4"
dev.off()  # to identify "null device" so the png file in the folder can be deleted;
getOption("device") # to set option to "RStudioGD"

    R: Update R version

    A. Update R through RGui

    • Open RGui through icon or open RGui from the directory (C:\Program Files\R\R-3.6.1\bin\x64\Rgui.exe)
    • In the Gui, enter the following.
    install.packages("installr")
library(installr)
    • Under “install” menu, click “Update R”.
    • Click through the dialogue boxes.

    Statistics: Meta-analysis. 1) Install dmetar package

    A. R code

    install.packages("tidyverse") 
install.packages("meta") 
install.packages("metafor")
devtools::install_github("MathiasHarrer/dmetar") 
# if not working, clone the package from github and unzip and install from local
devtools::install("C:/dmetar-master/dmetar-master")

    B. Error

    Error: (converted from warning) cannot remove prior installation of package ‘digest’

    C. Workaround

    • get library location: Sys.getenv(“R_LIBS_USER”)
    • close R program completely
    • Go to R library: C:\Program Files\R\R-3.6.1\library
    • Delete “digest” folder manually
    • Rerun R with above code and the error message will not appear again and the dmetar package will be successfully intstalled.