Statistical Analysis System

SAS/ETS, Statistical Analysis System Econometrics and Time Series. SAS Institute, Cary, North Carolina, 1983. 

Data were subjected to analysis of variance and regression analysis using the general linear model procedure of the Statistical Analysis System (40). Means were compared using Waller-Duncan procedure with a K ratio of 100. Polynomial equations were best fitted to the data based on significance level of the terms of the equations and values. 

SAS has always had and will maintain a central role in the data management, analysis, and reporting of clinical trial data. Because of the strong suite of SAS statistical procedures and the power of Base SAS programming, SAS remains a favorite of statisticians for the analysis of clinical trial data. Several companies have built their clinical trial data management and statistical analysis systems entirely with SAS software. More recently, SAS has offered SAS Drug Development as an industry solution that provides a comprehensive clinical trial analysis and reporting environment compliant with 21 CRF-Part 11. 

The initial multivariate analysis consisted of a principal component analysis on the raw data to determine if any obvious relationships were overlooked by univariate statistical analysis. The data base was reviewed and records containing missing data elements were deleted. The data was run through the Statistical Analysis System (SAS) procedure PRINCOMP and the results were evaluated. 

Statistical Analysis. Statistical analyses (two-way ANOVA) were performed by using the Statistical Analysis System (SAS, 1990). Means were compared by the least significant difference (LSD) test at a = 0.05. 

A further honing of proof quantification comes from the concept of application. Software can be broadly defined as standard (widely used, as with an operating system), customized [the multiple site development of a shell defined and written from a standard program, such as the development of a statistical analysis system (SAS) in a C-based language]. 

The analysis of variance (ANOVA) gives information on the significant effects. Data were analyzed using the general linear model (GLM) procedure from the Statistical Analysis System (SAS Institute, Cary, NC). A discussion and explanation of the statistics involved are given by Davies [19]. 

In the Toyama Bay Japanese effluent study, 20% endpoint effect values (e.g., LC20s for the D. magna assay and IC20s for the S. capricomutum assay), which are close approximations of TC values determined from NOEC and LOEC data (as in the Canadian study), were transformed into TU values and integrated into the PEEP formula. In applying the PEEP index concept to a designated series of wastewaters discharging to a common aquatic environment, it is paramount, of course, to use the same battery of bioassays and to report all of their toxicity responses with the same measurement endpoint and statistical analysis system (i.e., TC values for all effluents... 

Petrographic analysis of the separated macerals, density determinations, and elemental analyses were performed at Argonne National Laboratories. The ash content of these samples is less than 1%. The oxygen levels reported here are obtained by difference. Computer correlations of the resulting parameters were done using the Statistical Analysis System on the VS/CMS system at the ER E-Linden site. Linear-regression analyses are also performed with that system. In the correlation plots which follow, samples will be identified by coal rank and maceral group. 

Registry of Toxic Effects of Chemicals (Sub-)Structural Alerts Statistical Analysis System Aqueous solubility Structure-Activity Relationship Self-Consistent Field Structure Data File Sex Hormone Binding Globulin Simplified Molecular Line Entry System... 

Data Analysis. Unless otherwise mentioned, SAS software (7) was used to analyze suspensibility data and generate empirical equations. SAS (Statistical Analysis System) is a widely used data-analysis system that comprises a group of computer programs which are integrated in a way that allows efficient execution of numerous statistical routines. 

Medical Device Measurement Systems Statistical Analysis Systems Labeling System Electronic Document Management Systems... 

Crawford, C.G., Slack, J.R. and Hirsch, R.M. (1983) Nonparametric Tests for Trends in Water Quality Data using the Statistical Analysis System. United States Geological Survey Report, 83-550. 

The calculation procedures used are available in software of the Statistical Analysis System (SAS), version 82-3. Central processing unit time per output distribution on a main frame computer (IBM Model 3280) was around 20 seconds and cost per output distribution was less than 6. 

A three level four factor three response design of RSM was employed to optimize the carrot dehydration process. The four factors were drying temperature in HTST fluidized bed dryer, exposure time in HTST fluidized bed dryer, concentration of biopolymers and blanching time. The three responses were rehydration ratio, bulk density and carotenoid loss during the process. Second degree polynomial equations and Statistical Analysis System were used to fit the data for RSM. 

SAS . Statistical Analysis System. The most commonly used statistical analysis package within the pharmaceutical industry. 

Statistical Analysis. T-tests, Kruskall-Wallis and analyses of variances were performed using SAS, a statistical computer software program developed by Statistical Analysis Systems, Inc. 

The results of the DTS tests are shown in Table I. The values given are in MPa with the standard deviation indicated by the number in parentheses. All statistical information was generated with the general linear model program of the Statistical Analysis System software (5). Comparisons of the data were made with Duncan s Multiple Range Test (modified for unequal sample sizes) at p<0.5 ( -5). Values prece by an asterisk indicate no significant difference from each other. 

Each experiment was carried out in two replicates. Peak area count of each volatile compoxmd was obtained for each replicate. Analysis of variance (ANOVA) using a general linear model (GLM) procedure of the Statistical Analysis System (SAS, 2004, Cary, USA) was performed to evaluate differences between parameters. The parameters evaluated were type, cultivar, location, crop year, and interactions between them Means comparison between parameters was carried out by Duncan s multiple range test using SAS software. 

Efforts are being made to develop the component reliability database and statistical analysis system for an LMFBR (CORDS) on an engineering workstation. The CORDS is originally based on CREDO (Centralized Reliability Data Organization), a cooperative project between PNC and the USDOE, which ended in 1992. As a result of enhancement of the user-interface, it became possible to use the CORDS as an on-line handbook of the component failure rate. 

The color changes in the samples were monitored by measuring the Hunter L, a, b values of the pressurized and control fish samples using a Minolta Chromameter II reflectance equipment. The differences between the mean values were analyzed using the least significant difference (LSD) multiple comparison test of Steel and Torrie, (1960). The general linear model (GLM) procedure of the Statistical Analysis System (SAS) on McGill University mainframe was used. 

A combination of univariate statistics and plots allow exploration of a candidate model relative to these last two requirements. Bacterial bioluminescence 15-minute EC50 data for 20 metal ions (McCloskey et al. 1996, Appendix 8.1) and the recently developed softness index (Kinraide 2009) can be applied to illustrate this approach. The following statistical analysis system (SAS) code implements analyses with normality plots and tests of regression residuals (Figure 8.1 top). It also plots predicted and observed data (Figure 8.1 middle) and regression residuals versus the explanatory variable, 0, 0 (Figure 8.1 bottom). 

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