Appendix A Summary of Tasks. Appendix Table of Contents

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Appendix A Summary of Tasks Appendix Table of Contents Reporting Tasks...357 ListData...357 Tables...358 Graphical Tasks...358 BarChart...358 PieChart...359 Histogram...359 BoxPlot...360 Probability Plot...360 ScatterPlot...361 ContourPlot...361 SurfacePlot...362 Statistical Tasks...362 Descriptive...362 TableAnalysis...364 Hypothesis...365 ANOVA...368 Regression..... 372 Multivariate...376 Survival...377 SampleSize...378

356 Appendix A. Summary of Tasks

Appendix A Summary of Tasks The following tables provide a list of capabilities available in the reporting, graphical, and statistical tasks in the Analyst Application. In each table, the column indicates the dialog in which the corresponding capability appears. Capabilities with an entry of in the column are those that the task produces automatically. Note that Analyst also provides an online index of its statistical features. You can view the index by clicking on the menu and selecting Index. Reporting Tasks The following tables provide a list of capabilities available in the Analyst Application reporting tasks (Reports menu). Table A.1. Capabilities in the List Data Task Column heading split character Column heading style Column values, row identifier Double spacing Sequence numbers, row identifier Single spacing Sum selected columns Total number of observations

358 Appendix A. Summary of Tasks Table A.2. Capabilities in the Tables Tasks Cell format Formats for class values and statistics, supplied Formats for class values and statistics, user-defined Headings, empty class value combinations Labels, variables, and statistics Missing values as valid class levels Number of spaces, row titles Ordering, class values Summary column position Summary row position Text, empty cells Graphical Tasks The following tables provide a list of capabilities available in the Analyst Application graphical tasks (Graphs menu). Table A.3. Capabilities in the Bar Chart Tasks Analysis variable Bar appearance Bar outline color and width Bar text color, size, and font Frame options Horizontal bar statistics, display options Number of bars Order of bars Reference lines Statistic to chart, average Statistic to chart, cumulative frequency Statistic to chart, cumulative percent Statistic to chart, frequency Statistic to chart, percent

359 Table A.3. (continued) Statistic to chart, sum Three-dimensional chart Two-dimensional chart Vertical bar statistics, display options Table A.4. Capabilities in the Pie Chart Task Analysis variable Frequency variable Missing values Number of slices "Other" slice Slice and outline colors Slice angle Slice explosion Slice label type and placement Slice text color, size, and font Statistic to chart, average Statistic to chart, frequency Statistic to chart, percent Statistic to chart, sum Three-dimensional chart Two-dimensional chart Table A.5. Capabilities in the Histogram Task Bar and outline colors Bar pattern Exponential, fitted curve Fitted curve colors Lognormal, fitted curve Midpoints for histogram intervals Fit Fit

360 Appendix A. Summary of Tasks Table A.5. (continued) Normal, fitted curve Number of observations, vertical axis scale Percent of observations, vertical axis scale Proportion of observations, vertical axis scale Weibull, fitted curve Fit Fit Table A.6. Capabilities in the Box Plot Task Box and outline colors Constant, box width Notches Point color and symbol Proportional to p n, box width Proportional to log (n), box width Proportional to sample size n, box width Schematic style Skeletal style Table A.7. Capabilities in the Probability Plot Task Exponential, fitted curve Fitted curve color Fitted curve style and width Grid lines at percentiles Lognormal, fitted curve Normal, fitted curve Point color and symbol Weibull, fitted curve

361 Table A.8. Capabilities in the Scatter Plot: Two-Dimensional Task Line color Line style and width Point color and symbol Points connected to y =0 Points connected with straight lines Reference lines Table A.9. Capabilities in the Scatter Plot: Three-Dimensional Task Point color and symbol Points connected to x y plane Reference lines Rotation angle Tilt angle Table A.10. Capabilities in the Contour Plot Task Bivariate interpolation Interpolate Contour line labeling Interpolation / smoothing Interpolate Legend display Linear interpolation Interpolate Number of levels Partial spline interpolation Interpolate Pattern line density and angle Pattern outline color Pattern style Spline interpolation Interpolate

362 Appendix A. Summary of Tasks Table A.11. Capabilities in the Surface Plot Task Bivariate interpolation Interpolate Interpolation / smoothing Interpolate Linear interpolation Interpolate Partial spline interpolation Interpolate Reference lines Rotation angle Spline interpolation Interpolate Surface colors Surface side walls Tilt angle Statistical Tasks The following tables provide a list of capabilities available in the Analyst Application statistical tasks ( menu). Table A.12. Capabilities in the Descriptive: Summary Task Box-and-whisker plot Coefficient of variation Corrected sum of squares Histogram Kurtosis Maximum Mean Median Minimum Number of missing observations Number of observations Output appearance Output Probability of t Range

363 Table A.12. (continued) Skewness Standard deviation Standard error Student s t Sum Uncorrected sum of squares Variance Table A.13. Capabilities in the Descriptive: Distributions Task Box-and-whisker plot Descriptive statistics Exponential, fitted distribution Fit Extreme observations Histogram Lognormal, fitted distribution Fit Median Moments Normal, fitted distribution Fit Percentiles Probability plot Quantile-quantile plot Quantiles Sign statistic Signed rank statistic for location Weibull, fitted distribution Fit

364 Appendix A. Summary of Tasks Table A.14. Capabilities in the Descriptive: Correlations Task Confidence ellipses Corrected SSCP matrix Covariances Cronbach s alpha Descriptive statistics Hoeffding s D Kendall s tau-b p-values Pearson correlations Scatter plots Spearman correlations SSCP matrix Table A.15. Capabilities in the Descriptive: Frequency Counts Task Bar charts Cumulative frequencies Tables Cumulative percentages Tables Frequencies Tables Order, variable levels Input Percentages Tables Table A.16. Capabilities in the Table Analysis Task Chi-square statistics Fisher s exact test for rc tables Frequencies Tables Likelihood ratio chi-square Mantel-Haenszel statistics McNemar s test for 22 tables Measures of agreement

365 Table A.16. (continued) Measures of association Odds ratios for 22 tables Order, variable levels Pearson chi-square Pearson correlation coefficient Percentages Simple kappa coefficient Spearman correlation coefficient Weighted kappa coefficient Input Tables Table A.17. Capabilities in the Hypothesis : One-Sample Z-test for a Mean Task Alternative hypotheses Bar chart Box-and-whisker plot Confidence intervals Mean comparison value Normal distribution plot Population standard deviation Population variance Power analysis Table A.18. Capabilities in the Hypothesis : One-Sample t-test for a Mean Task Alternative hypotheses Bar chart Box-and-whisker plot Confidence intervals Mean comparison value Power analysis t distribution plot

366 Appendix A. Summary of Tasks Table A.19. Capabilities in the Hypothesis : One-Sample Test for a Proportion Task Alternative hypotheses Bar chart Confidence intervals Normal distribution plot Table A.20. Capabilities in the Hypothesis : One-Sample Test for a Variance Task Alternative hypotheses Box-and-whisker plot Confidence intervals Probability distribution plot Variance comparison value Table A.21. Capabilities in the Hypothesis : Two-Sample t-test for Task Alternative hypotheses Bar chart Box-and-whisker plot Confidence intervals Mean comparison value plot Power analysis Stacked data t distribution plot Unstacked data

367 Table A.22. Capabilities in the Hypothesis : Two-Sample Paired t-test for Task Alternative hypotheses Bar chart Box-and-whisker plot Confidence intervals Mean comparison value plot Power analysis t distribution plot Table A.23. Capabilities in the Hypothesis : Two-Sample Test for Proportions Task Alternative hypotheses Bar chart Confidence intervals Normal distribution plot Stacked data Unstacked data Table A.24. Capabilities in the Hypothesis : Two-Sample Test for Variances Task Alternative hypotheses Box-and-whisker plot Confidence intervals Probability distribution plot Stacked data Unstacked data

368 Appendix A. Summary of Tasks Table A.25. Capabilities in the ANOVA: One-Way ANOVA Task Bonferroni t-test Box and whisker plot Duncan multiple-range test comparisons plots Power analysis R-square statistic Residual plots of homogeneity of variance Tukey HSD test Welch s variance-weighted ANOVA Table A.26. Capabilities in the ANOVA: Nonparametric One-Way ANOVA Task Ansari-Bradley test Exact p-values Klotz test Kruskal-Wallis test Median test Mood test Savage test Siegel-Tukey test Van der Waerden test Wilcoxon test

369 Table A.27. Capabilities in the ANOVA: Factorial ANOVA Task Adjusted R-square statistic Bonferroni t-test Covariance ratio Crossed effects DFFITS Duncan multiple-range test Factorial models Influence plots Interaction effects Least-squares means Leverage comparisons plots building Power analysis Predicted values Prediction limits R-square statistic Residual plots Residual values Residuals, ordinary Residuals, standardized Residuals, studentized Tukey HSD test Type 1, 2, 3, 4 sum of squares Weighted least squares

370 Appendix A. Summary of Tasks Table A.28. Capabilities in the ANOVA: Linear s Task Adjusted R-square statistic Bonferroni t-test Classification effects Covariance ratio Crossed effects DFFITS Duncan multiple-range test Factorial models Influence plots Interaction effects Intercept Least-squares means Leverage comparisons plots building Multivariate tests Nested effects Parameter estimates Polynomial effects Power analysis Predicted plots Predicted values Prediction limits R-square statistic Residual plots Residual values Residuals, ordinary Residuals, standardized Residuals, studentized Scatter plots Tukey HSD test Type 1, 2, 3, 4 sum of squares Weighted least squares

371 Table A.29. Capabilities in the ANOVA: Repeated Measures Task Ante-dependence covariances, first order Autoregressive covariances, first order Chi-square test, likelihood ratio Classification effects Compound symmetry covariances Confidence limits, covariance estimates Confidence limits, parameter estimates Covariance structures Crossed effects Factorial models Fitting information Huynh-Feldt covariances Information criteria summary Interaction effects Intercept Least-squares means Likelihood ratio test plots building Nested effects Parameter estimates Polynomial effects Predicted plots Predicted values Prediction limits Repeated effect Residual plots Residual values Scatter plots Subject effect Toeplitz covariances Type 1, 2, 3 sum of squares Unstructured covariances Variance components structure

372 Appendix A. Summary of Tasks Table A.30. Capabilities in the ANOVA: Mixed s Task Classification effects Confidence level Confidence limits, covariance parameter estimates Confidence limits, fixed effects estimates Confidence limits, random effects estimates Covariance parameter estimates Crossed effects Estimation methods Factorial models Fitting information Fixed effects Interaction effects Intercept, fixed effects Least-squares means effects Maximum likelihood estimation plots, fixed effects Minimum variance quadratic unbiased estimation building Nested effects Polynomial effects Predicted means Predicted value plots Predicted values, including random effects Random effects REML Residual maximum likelihood estimation Residual plots Satterthwaite method, fixed effects Scatter plots Solution, fixed effects parameters Solution, random effects parameters Types 1, 2, 3 estimation Types 1, 2, 3 tests, fixed effects Variance components tests

373 Table A.31. Capabilities in the Regression: Simple Task Adjusted R-square statistic Coefficient of variation Confidence limits Confidence limits for estimates Correlation matrix of estimates Covariance matrix of estimates Covariance ratio Cubic model DFFITS Influence plots Leverage Normal probability-probability plot Normal quantile-quantile plot Power analysis Predicted values Prediction limits Quadratic model R-square statistic Residual plots Residual values Residuals, ordinary Residuals, standardized Residuals, studentized Scatter plots Standardized regression coefficients Table A.32. Capabilities in the Regression: Linear Task Adjusted R-square model selection Adjusted R-square statistic Akaike s information criterion Amemiya s prediction criterion Asymptotic covariance matrix

374 Appendix A. Summary of Tasks Table A.32. (continued) Backward elimination model selection Bayesian information criterion Coefficient of variation Collinearity analysis Confidence limits for estimates Correlation matrix of estimates Covariance matrix of estimates Covariance ratio DFFITS Durbin-Watson statistic Forward model selection Heteroscedasticity test Influence plots Intercept Leverage Mallows Cp model selection Mallows Cp statistic Maximum R-square improvement model selection Minimum R-square improvement model selection Multivariate statistics Normal probability-probability plot Normal quantile-quantile plot Partial correlations Power analysis Predicted values Prediction limits R-square model selection R-square statistic Residual plots Residual values Residuals, ordinary Residuals, standardized Residuals, studentized Scatter plots Schwarz s bayesian criterion

375 Table A.32. (continued) Semi-partial correlations Standardized regression coefficients Stepwise model selection Stepwise regression Tolerance values for estimates Type 1 sum of squares Type 2 sum of squares Variance inflation factors Weighted least squares Table A.33. Capabilities in the Regression: Logistic Task Association of predicted probabilities and observed responses Backward elimination model selection Best subset model selection CI displacement Classification effects Classification table Conditional odds ratios Confidence limits Correlation matrix of estimates Covariance matrix of estimates Crossed effects Deviance residuals DFBetas Difference in chi-square residuals Difference in deviance residuals Dispersion parameter Factorial models Fit statistics Forward model selection Goodness-of-fit statistics Influence plots

376 Appendix A. Summary of Tasks Table A.33. (continued) Interaction effects Leverage Likelihood ratio Odds ratio estimates Pearson residuals Polynomial effects Predicted values Prior probabilities Probability cutpoints Profile likelihood limits Residual plots Residual values Response profile ROC curve Standardized estimates Stepwise model selection Wald limits Table A.34. Capabilities in the Multivariate: Principal Components Task Analysis of correlation matrix Analysis of covariance matrix Analysis of uncorrected matrices Principal component scores Principal components plot Scree plot Save Data

377 Table A.35. Capabilities in the Multivariate: Canonical Correlation Task Canonical redundancy statistics Canonical variable plot Canonical variable scores Save Data Correlations of regression coefficients Number of canonical variables Partial correlations Partial variables Variables Regression analysis Semi-partial correlations Squared multiple correlation Standard error of coefficients Standardized regression coefficients t statistic and probability Table A.36. Capabilities in the Survival: Life Tables Task Censoring values Confidence intervals Hazard function plots Life table method Probability density function plots Product-limit estimation method Strata endpoints Survival estimates Survival function plots Methods Methods Methods

378 Appendix 1. Summary of Tasks Table A.37. Capabilities in the Survival: Proportional Hazards Task Backward elimination model selection Best subset model selection Censoring values Confidence limits of hazard ratio Methods Correlations of parameter estimates Methods Covariances of parameter estimates Methods Failure time ties, Breslow approximate likelihood method Methods Failure time ties, discrete logistic model method Methods Failure time ties, Efron approximate likelihood method Methods Failure time ties, exact conditional probability method Methods Forward model selection Global hypothesis test Stepwise model selection Survival function plots The Sample Size tasks provide sample size and power calculations for several types of analyses and study designs. Power curves are available with each task. The types of sample size analyses available in the Analyst Application are as follows: one-sample t-test one-sample confidence interval one-sample equivalence paired t-test paired confidence interval paired equivalence two-sample t-test two-sample confidence interval two-sample equivalence one-way ANOVA

The correct bibliographic citation for this manual is as follows: SAS Institute Inc., The Analyst Application, First Edition, Cary, NC: SAS Institute Inc., 1999. 476 pp. The Analyst Application, First Edition Copyright 1999 SAS Institute Inc., Cary, NC, USA. ISBN 1 58025 446 2 All rights reserved. Printed in the United States of America. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, by any form or by any means, electronic, mechanical, photocopying, or otherwise, without the prior written permission of the publisher, SAS Institute, Inc. U.S. Government Restricted Rights Notice. Use, duplication, or disclosure of the software by the government is subject to restrictions as set forth in FAR 52.227 19 Commercial Computer Software-Restricted Rights (June 1987). SAS Institute Inc., SAS Campus Drive, Cary, North Carolina 27513. 1st printing, October 1999 SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. indicates USA registration. IBM, ACF/VTAM, AIX, APPN, MVS/ESA, OS/2, OS/390, VM/ESA, and VTAM are registered trademarks or trademarks of International Business Machines Corporation. indicates USA registration. Other brand and product names are registered trademarks or trademarks of their respective companies. The Institute is a private company devoted to the support and further development of its software and related services.