clinical SAS Statistical Analysis Software
Clinical SAS Statistical Analysis Software is the application of SAS technology to clinical domain for clinical trial data analysis in pharmaceutical/biotech and clinical research
SAS is widely used in clinical trial data analysis in pharmaceutical, biotech and clinical research companies.
Statistical Analysis Software (SAS) is a biostatistical tool used to manage and generate tables, listings and graphs for clinical study reports
SAS Statistical Analysis System is a statistical software suite developed by SAS Institute for data management, advanced analytics, multivariate analysis, business intelligence, criminal investigation, and predictive analytics.
The construction of a Williams design and randomization in cross-over clinical trials using SAS
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A Williams design is a special and useful type of cross-over design. Balance is achieved by using only one particular Latin square if there are even numbers of treatments, and by using only two appropriate squares if there are odd numbers of treatments. PROC PLAN of
Design and analysis of equivalence clinical trials via the SAS system
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An equivalence clinical trial typically is conducted to demonstrate that there is no clinically significant difference between a standard and an experimental treatment. The study is designed with the desired outcome being equivalence in efficacy, while immediate toxicity
Analyzing quality of life (QOL) endpoints in clinical trials via the SAS system
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The cure for many chronic diseases, such as cancer and AIDS, remains elusive. Clinical research increasingly has focused more on maximizing patient QOL because improvements in survival and response to treatment have become more difficult to achieve. Patient quality
Imputation techniques using SAS software for incomplete data in diabetes clinical trials
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Missing data are common in clinical trials. In longitudinal studies missing data are mostly related to drop-outs. Some drop-outs appear completely at random. The source for other drop-outs is withdrawal from trials due to lack of efficacy. For the latter case the standard
A new SAS macro for flexible parametric survival modeling: applications to clinical trials and surveillance data
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Parametric models are useful in several applications, including health economic evaluation, cancer surveillance and event prediction. Flexible parametric models extend standard parametric models (eg Weibull) to increase the flexibility of the shape of the hazard function
Performance Evaluation of Clinical SAS Programmer
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Despite highly efficient hiring practices a firm have, it is important to monitor and evaluate the performance of SAS programmers. Periodic performance evaluation is necessary to minimize the cost associated with human resource turnover, and to ensure
Industry Standard Good Programming Practice for Clinical Trials (Using SAS )
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ABSTRACT Good Programming Practices help programmers write code that is clear, easily maintained and reusable. This results in improved efficiency in both the development and running of code as well as reducing the risk of making errors. Over the last year, an editorial
Using SAS proc power to perform model-based power analysis for clinical pharmacology studies
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In this paper, we demonstrate that many hypothesis testing problems in clinical pharmacology studies can be reformulated as a one-or two-sample t-test or equivalence test. Thereby one can use SAS Proc Power to perform the power analysis. Sample
Clinical trials management on the internet I: Using LATEX and SAS to produce customized forms
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In clinical trials, forms are used to gather data which is then entered into a database. Paper- based forms are still the standard for data collection, due to portability, stability, and storage considerations. In producing forms, SAS /IntrNet (a SAS product which works with the
Clinical trials versus health outcomes research: SAS /STAT versus SAS enterprise miner
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Clinical trials typically involve a random selection of subjects to receive an experimental treatment or a control. They often use a minimal sample size, a short term rather than a long term period of study, and clinical trials often use surrogate endpoints. Inclusion/exclusion
P2644 The Surgery after Stent ( SAS ) Registry: a gender-based analysis on clinical outcomes in women undergoing cardiac and non-cardiac surgery
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Background: Whether long-term outcomes of unprotected left main coronary artery (ULMCA) bifurcation lesions treated by second-generation drug-eluting stent (G2-DES) implantation depend on the stenting strategies remain unclear. Purpose: We aimed to clarify the effects of
Adaptive design using SAS and WinBUGS: application to an acute stroke clinical trial
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Page 1. Adaptive design using SAS and WinBUGS: application to an acute stroke clinical trial David Spiegelhalter MRC Biostatistics Unit, Cambridge Chris Weir Robertson Centre for Biostatistics, Glasgow RSS meeting on adaptive design: October 6th 2004 1 Page 2. Adaptive
Clinical trials management on the internet II. Using LATEX, PostScript, and SAS to produce barcode label sheets
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In clinical trials, it is often necessary to print labels with barcodes to identify samples. The availability of open-source tools for barcode management is still somewhat limited. Until recently, no LATEX tools existed for the manipulation and encoding of barcodes. Using
SAS : Symmetric Analysis of Z-Spectra, a Method to Evaluate B0 Correction Techniques for CEST Data in Clinical Systems Using Non-Exchanging Phantoms
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Introduction: Chemical Exchange Saturation Transfer (CEST) data requires correction for B0 variations, which alter the effective off-resonance applied frequencies on a voxel-by-voxel basis. Currently research groups worldwide use multiple methods of correcting for B0
Quality Assurance: Best Practices in Clinical SAS Programming
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SAS programmers working on clinical reporting projects are often under constant pressure of meeting tight timelines, producing best quality SAS code and of meeting needs of customers. As per regulatory guidelines, a typical clinical report or dataset generation using
The New Tradition: SAS Clinical Data Integration
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Base SAS programming has been around for a very long time. And over that time, there have been many changes. New and enhanced procedures, new features, new functions and even operating systems have been added. Over time, there have been many windows and
Monitoring Clinical Trials with a SAS Risk-Based Approach
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With global regulatory encouragement, the life sciences industry is gaining momentum to embrace a risk-based approach to the monitoring of clinical trials. Typical to pharmaceutical organizations, there is wide variation regarding the level and speed of adoption
Practical application of SAS Clinical Data Integration Server for conversion to SDTM data
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Conversion of legacy clinical data into a standardized data model consists of different steps from annotating the CRF, preparing the mapping into the CDISC SDTM model to producing metadata reports and CRT-DDS (define. xml). In order to accelerate the conversion process
SAS Clinical Standards Toolkit 1.4
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3 Copyright 201 SAS Institute Inc. All rights reserved. What is the SAS Clinical Standards Toolkit (CST) Page 4. 4 Copyright 201 SAS Institute Inc. All rights reserved. What is the SAS Clinical Standards Toolkit Framework to primarily support Clinical Research activities. Initially focusing
Clinical knowledge helps SAS programmers in the pharmaceutical industry get job done better
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ABSTRACT SAS programming in the pharmaceutical industry is not a pure programming job like that in the IT industry. It requires more understanding and knowledge on the business side, ie the complicated nature of clinical trial and clinical trial data. In this sense, Clinical
SAS /AF Application in Sequential Clinical Trials
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Competition in pharmaceutical drug development is intense [Senn: 1997]. Planning and conducting clinical trials to confirm drug efficacy is a complicated procedure, and software aids are very desirable for those managing this activity. This paper gives a brief account of
SAS Drug Development as a platform governing data standards specification and clinical data exchange between pharmaceutical organizations
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An innovative set-up is described here that consists of upfront clinical study data specifications in SAS Drug Development(SDD) using CDISC standard data models. This set-up enables sponsors to automate the exchange of specifications and instructions to their
Data Migration from Oracle Clinical to. XML using SAS
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The main strength of XML data structure consists in allowing the user greater flexibility in managing data in several platforms. The work performed and presented in this poster was motivated by a Sponsors request to export data contained in an Oracle Clinical database
Tips for Creating SAS -Based Applications for Oracle Clinical
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Oracle Clinical (OC) is database management system used to support clinical trials processes. There is an enormous amount of data and metadata stored in OC beyond the data points collected on a case report form, which can be used as the basis for developing
Managing Clinical Data Standards: An Introduction to SAS Clinical Data Integration
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As the adoption of industry data standards grows, organizations must consider how to effectively implement and manage data standards across a large often global user base. SAS Clinical Data Integration is built upon a centralized metadata repository that is ideal
QC the Qualitative Part of Clinical Data in SAS Datasets
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In the Pharmaceutical industry, qualitative descriptions are prevalent in clinical data (eg, lab, adverse events, etc.). Also often encountered are variables formatted with character values (eg, metadata in SDTM and ADaM formats). To spot misspelled words in qualitative data and
SAS /PH- Clinical Software: CANDA Implementation Strategies
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SAS /PH-Clinicar software is currently used for a variety of clinical data review needs w~ hin the pharmaceutical and biotechnology industries. Certainly, one of the most critical needs for effective delivery of clinical information comes when implementing a Computer-assisted
MANAGING CUSTOM DATA STANDARDS IN SAS CLINICAL DATA INTEGRATION
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Page 1. Copyright 201 SAS Institute Inc. All rights reserved. MANAGING CUSTOM DATA STANDARDS IN SAS CLINICAL DATA INTEGRATION MELISSA R. MARTINEZ PHUSE 2014 Page 2. Copyright 201 SAS Institute Inc. All rights reserved. AGENDA Data Standards
Inverse Prediction Using SAS Software: A Clinical Application
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An important application of regression methodology is in the area of prediction. Oftentimes investigators are interested in predicting a value of a response variable (Y) based on the known value of the predictor variable (X). However, sometimes there is a need to predict a
Developing Custom SAS Studio Tasks for Clinical Trial Graphs
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ABSTRACT SAS Studio provides point-and-click tasks for basic statistics, biostatistics models, and statistical graphs. SAS Studio users can create their own Custom Tasks by modifying existing tasks or writing new ones using simple text commands from Apache
Application of Criterion I2 in Clinical Trials Using SAS
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The goal of this paper is to demonstrate how meta-analyses criteria (specifically, I2 and Cochrans Q) can be calculated using SAS software and applied to the examination of the heterogeneity across subgroups. Some European regulatory authorities require an analysis
Comparing JMP and SAS for Validating Clinical Trials
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When validating clinical trial analyses, an independent programmer typically confirms the results. Most companies use SAS as the standard software for performing analyses and generating results to submit to regulatory agencies. Validation requires replicating the
Using SAS Clinical Data Integration Server to Implement and Manage CDISC Standards
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ABSTRACT The SAS Metadata Server is a core component of all SAS 9 solutions. It delivers the power to integrate, share, centrally manage, and leverage metadata across entire organizations. Through these capabilities, standard data models such as the CDISC
Clinical Data Dashboards for Centralized Monitoring Using SAS and Microsoft SharePoint
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In recent guidance on risk-based monitoring practices, the Food and Drug Administration identified options for monitoring the data quality of a clinical investigation. Centralized monitoring is a practice in which clinical data management, statisticians, and/or clinical
P15 Using SAS macros to automate data reports in multi-center clinical trials
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Despite stringent data collection, entry, and editing procedures designed to ensure quality data, a number of data errors, inevitably, will exist in most, if not all, databases. The identification and correction of errors occurs on a routine basis during the creation and
MAKS: A validated SAS Macro Library for Clinical Data in the CDISC SDTM Structure
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ABSTRACT MAKS ( Makros zur Auswertung Klinischer Studien) is a CDISC SDTM based library of validated SAS macros for reporting data from clinical studies. The macros will be made available to a wide community. Robustness therefore was an important requirement
Design, Analysis and Review Tools for Clinical Drug Development Using SAS Object-Oriented Products
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The business reengineering of clinical drug development in the Medical Affairs Department at Genentech resulted in an innovative process using several SAS object-oriented products. This effort resulted in the Design, Analysis and Review Tools (DART) accessed
Evaluating Safety Signals in Clinical Trials: the Dirichlet-NBD Model Implementation with SAS
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In clinical research, it is often necessary to analyze a group of drug adverse events jointly as well as to analyze them individually. The Dirichlet-NBD model, a statistical model with the combination of both the Negative Binomial Distribution (NBD) and the Dirichlet Multinomial