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Stata Technical Bulletin

an14 SAS’s new technical journal

Joseph Hilbe, Editor, STB, FAX 602-860-1446

SAS users will be pleased to learn that the Institute is publishing a new technical journal called Observations: The Technical
Journal for
sas Software Users. The first issue was just published (Fourth Quarter, 1991). Subscription cost is $49 per year for
the quarterly. No diskettes are provided.

If you are interested contact The SAS Institute, SAS Circle, Box 8000, Cary, NC 27512-8000. The telephone number is
919-677-8000 and the
FAX number is 919-677-8123.

an15 Regression with Graphics released

Joseph Hilbe, Editor, STB, FAX 602-860-1446

Brooks/Cole Publishing Company, a division of Wadsworth, will release Lawrence Hamilton’s new text entitled Regression
with Graphics
(ISBN 0-534-15900-1) this month (anticipated release date of November 18). Written as a sequel to his earlier
Modern Data Analysis: A First Course in Applied Statistics, this text is aimed at a second semester undergraduate course in
applied statistics or data analysis. It is also appropriate for graduate social science courses where students should become more
intimately familiar with regression diagnostics,
EDA and graphical techniques, robust methods, logistic regression, and elementary
principal components and factor analysis. Text material is heavily supplemented with numerous graphs that were produced with
Stata and Stage.
STB-1, -2, and -3 inserts provided by Dr. Hamilton were based on parts of the text.

There are few general texts on regression that directly address robust and logistic regression. Hamilton has done excellent
work in making otherwise rather difficult material accessible to the undergraduate reader. His discussion of logistic regression
follows that of Hosmer & Lemeshow’s
Applied Logistic Regression, John Wiley & Sons, 1989. Stata users will find it particularly
useful when using
logiodd2 (see sqv1.3).

The following Table of Contents is based on a pre-publication manuscript copy. Expect minor changes with the final release.
Each chapter ends with a Conclusion, Exercises, and Notes (not shown).

Chapter 1: VARIABLE DISTRIBUTIONS— The Concord Water Study; Mean, Variance, and Standard Deviation; Normal Distributions; Median
and Interquartile Range; Boxplots; Symmetry Plots; Quantile Plots; Quantile-Quantile Plots; Quantile-Normal Plots; Power Transformations; Selecting
an Appropriate Power

Chapter 2: BIVARIATE REGRESSION ANALYSIS— The Basic Linear Model; Ordinary Least Squares; Scatterplots and Regression; Predicted
Values and Residuals; R , Correlation, and Standardized Regression Coefficients; Reading Computer Output; Hypothesis Tests for Regression Coefficients;
Confidence Intervals; Regression through the Origin; Problems with Regression; Residual Analysis; Power Transformations; Understanding Curvilinear
Regression

Chapter 3: BASICS OF MULTIPLE REGRESSION— Multiple Regression Models; A Three-Variable Example; Partial Effects; Variable Selection;
A Seven-Variable Example; Standardized Regression Coefficients; t-Tests and Confidence Intervals for Individual Coefficients; F-Tests for Sets of
Coefficients; Multicollinearity; Search Strategies; Interaction Effects; Intercept Dummy Variables; Slope Dummy Variables; Oneway Analysis of
Variance; Twoway Analysis of Variance

Chapter 4: REGRESSION CRITICISM— Assumptions of Ordinary Least Squares; Correlation and Scatterplot Matrices; Residual versus Predicted
Y Plots; Autocorrelation; Nonnormality; Influence Analysis; More Case Statistics; Symptoms of Multicollinearity

Chapter 5: REGRESSION WITH TRANSFORMED VARIABLES— Transformations and Curves; Choosing Transformations; Diagnostics;
Conditional Effect Plots; Comparing Curves

Chapter 6: ROBUST REGRESSION— A Two-Variable Example; Goals of Robust Regression; M-Estimation and Iteratively Reweighted Least
Squares; Calculation by IRLS; Standard Errors and Tests for M-Estimates; Using Robust Estimation; A Robust Multiple Regression; Bounded-Influence
Regression

Chapter 7: LOGIT REGRESSION— Limitations of Linear Regression; The Logit Regression Model; Estimation; Hypothesis Tests and Confidence
Intervals; Interpretation; Statistical Problems; Influence Statistics for Logit Regression; Diagnostic Graphs

Chapter 8: PRINCIPAL COMPONENTS AND FACTOR ANALYSIS— Introduction to Principal Components and Factor Analysis; A Principal
Components Analysis; How Many Components?; Rotation; Factor Scores; Graphical Applications: Detecting Outliers and Clusters; Principal Factor
Analysis; An Example of Principal Factor Analysis; Maximum Likelihood Factor Analysis

Appendices: Population and Sampling Distributions; Computer-Intensive Methods; Matrix Algebra; Statistical Tables

Anyone interested in obtaining a copy of the book should contact Wadsworth at 800-354-9706.

crc11 Drawing random samples

The syntax of sample is

sample # [if exp [in range [, by ggruppaars") ]

sample draws a # percent sample of the data in memory, thus discarding 100-# percent of the observations. Observations not



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