Applied Statistics and the SAS Programming Language

Abstract

I. APPLIED STATISTICS AND SAS SOFTWARE. 1. A SAS Tutorial. Introduction. Computing with SAS Software: An Illustrative Example. Enhancing the Program. SAS Procedures. Overview of the SAS Step. Syntax of SAS Procedures. Comment Statements. References. 2. Describing Data. Introduction. Describing Data. More Descriptive Statistics. Descriptive Statistics Broken Down by Subgroups. Frequency Distributions. Bar Graphs. Plotting Data. Creating Summary Sets with PROC MEANS an PROC UNIVARIATE. Outputting Statistics Other than Means. Creating a Summary Set to Contain a Median. 3. Analyzing Categorical Data. Introduction. Questionnaire Design and Analysis. Adding Variable Labels. Adding Labels (Formats). Recoding Data. Using a Format to Recode a Variable. Two-way Frequency Tables. A Shortcut Way of Requesting Multiple Tables. Computing Chi-square From Frequency Counts. A Useful Program for Multiple Chi-square Tables. McNemar's Test for Paired Data. Odds Ratios. Relative Risk. Chi-square Test for Trend. Mantel-Haenszel Chi-square for Stratified Tables and Meta Analysis. Check all that Apply Questions. 4. Working with Date and Longitudinal Data. Introduction Processing Date Variables. Longitudinal Data. Most Recent (or Last) Visit per Patient. Computing Frequencies on Longitudinal Sets. 5. Correlation and Regression. Introduction. Correlation. Significance of a Correlation Coefficient. How to Interpret a Correlation Coefficient. Partial Correlations. Linear Regression. Partitioning the Total Sum of Squares. Plotting the Points on the Regression Line. Plotting Residuals and Confidence Limits. Adding a Quadratic Term to the Regression Equation. Transforming Data. Computing Within-subject Slopes. 6. T-Tests and Nonparametric Comparisons. Introduction. T-Test: Testing Differences Between Two Means. Random Assignment of Subjects. Two Independent Samples: Distribution Free Tests. One-Tailed versus Two-Tailed Tests. Paired T-Tests (Related Samples). 7. Analysis of Variance. Introduction. One-Way Analysis of Variance. Computing Contrasts. Analysis of Variance: Two Independent Variables. Interpreting Significant Interactions. N-Way Factorial Designs. Unbalanced Designs: PROC GLM. Analysis of Covariance. 8. Repeated Measures Designs. Introduction. One-Factor Experiments. Using the REPEATED Statement of PROC ANOVA. Two-Factor Experiments with a Repeated Measure on One Factor. Two-Factor Experiments with Repeated Measures on Both Factors. Three-Factor Experiments with a Repeated Measure on the Last Factor. Three-Factor Experiments with Repeated Measures on Two Factors. 9. Multiple Regression Analysis. Introduction. Designed Regression. Nonexperimental Regression. Stepwise Regressions. Creating and Using Dummy Variables. Logistic Regression. 10. Factor Analysis. Introduction. Types of Factor Analysis. Principle Components Analysis. Oblique Rotations. Using Communalities Other than One. How to Reverse Item Scores. 11. Psychometrics. Introduction. Using SAS Software to Score a Test. Generalizing the Program for a Variable Number of Questions. Creating a Better Looking Table Using PROC TABULATE. A Complete Test Scoring and Item Analysis Program. Test Reliability. Interrater Reliability. II. SAS PROGRAMMING. 12. The SAS INPUT Statement. Introduction. List Directed Input: Values Separated By Spaces. Reading Comma Delimited Data. Using INFORMATS with List Directed Data. Column Input. Pointers and Informats. Reading More than One per Subject. Changing the Order and Reading a Column More Than Once. Informat Lists. Holding the Line - Single and Double Trailing @'s. Suppressing the Error Messages for Invalid Data. Reading Unstructured Data. 13. External Files: Reading and Writing and System Files. Introduction. in the Program Itself. Reading ASCII from and External File. INFILE Options. Writing ASCII or Raw Data to an External File. Creating a Permanent SAS Set. Reading Permanent SAS Sets. How to Determine the Contents of a SAS Set. Permanent SAS Sets with Formats. Working with Large Sets. 14. Set Subsetting, Concatenating, Merging, and Updating. Introduction. Subsetting. Combining Similar from Multiple SAS Sets. Combining Different from Multiple SAS Sets. Table Look Up. Updating a Master Set from an Update Set. 15. Working with Arrays. Introduction. Substituting One Value for Another for a Series of Variables. Extending Example 1 to Convert All Numeric Values o 999 to Missing. Converting the Value of N/A (not applicable) to a Character Missing Value. Converting Heights and Weights from English to Metric Units. Temporary Arrays. Using a Temporary Array to Score a Test. Specifying Array Bounds. Temporary Arrays and Array Bounds. Implicitly Subscripted Arrays. 16. Restructuring SAS Sets Using Arrays. Introduction. Creating a New Set With Several Observations per Subject from a Set with One Observation per Subject. Another Example of Creating Multiple Observations from a Single Observation. Going from One Observation per Subject to Many Observati