Software
The developers at PNLSC produce bespoke commercial software systems tailored for client specific applications
RR Estimation
The paper "Facilitating meta-analyses by deriving relative effect and precision
estimates for alternative comparisons from a set of estimates presented by
exposure level or disease category" (Jan Hamling et al., Statistics in
Medicine, 2008) describes software for calculating estimates.
Jan Hamling, in collaboration with Mathias Ambuehl of Consult AG in Berne, have developed the Excel and SAS software described in this paper.
Available here for download are the two versions as discussed in that paper, one using Excel with VBA macros and the other using SAS.
The following updated versions include the original RREst analysis (as detailed in the paper) but now incorporate trend analyses. The SAS and R versions also include Goodness of Fit:-
Excel Spreadsheet Version
Download the spreadsheet:
RREst_trend.xlsm
Download the documentation: RREst_Trend.pdf
SAS Version
Download the documentation: RREst
_trend_SAS.pdf
Download the SAS module
RREst_trend.SAS (zip file): RREst_trend_SAS.zip
R Version (web
version, opens in a new tab)
https://roelee.shinyapps.io/R_RRest/
Download the R Code R_ RREst.R (zip file)
R_RRest.zip
Goodness of Fit (analysis in SAS & R versions only):-
Download the document: Goodness of fit tests for fitted RRs.pdf
Testing of RREst Trend in
R, SAS & Excel:-
Download a
zip file containing the test documents, input files and results
The original versions are still available here:-
Excel Spreadsheet Version
Download the spreadsheet: RREst.xls
Download the documentation: RREst.pdf
SAS Version
Download the documentation: RREst SAS.doc
Download the SAS modules (zip file):
RREst_SAS.zip (contains RREst.SAS & Examples RREst.SAS)
IMASS (International Mortality And Smoking Statistics)
A comprehensive Excel database system with mortality and smoking related data from 30 different countries.
Full details and downloads for the IMASS system
RoeLee & Peer Review
Whilst originally developed by P N Lee Statistics and Computing Ltd, the RoeLee
system is now developed and supported by
Roelee Statistics Ltd
RoeLee
The RoeLee system arose from
original ideas of Dr. Francis Roe, a medically qualified pathologist in
collaboration with Peter
Lee. RoeLee is a system for recording, reporting and statistical analysis of histopathology data
from long-term experimental carcinogenicity studies. Developed by Dr. John Fry
over more than 20 years, the system now has an extremely wide range of
facilities, and its range of use has widened considerably. The main areas of its
use include:
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Peer Review
This system enables detailed Peer
Review of histopathology data. The data need not have been read initially on RoeLee, as Peer Review will accept data from existing systems such as Pathdata
and Xybion. This allows users to carry out peer reviews whilst retaining their
current data recording system and working environment.