One of the interesting observations in my first few months in US: there is no price printed in the new mail stamps! It is interesting because as a former student of economics, I think US Post system did a nice attempt to beat the so called “menu cost” which should honor to Harvard economist Mankiw. […]
Category: SAS
What’s in a name – SQL Join or SET?
Did that set off a trigger for you? It did for my SAS SQL 1: Essentials class, packed with SQL and SAS programmers alike. To clarify matters I pulled up some examples to help get the differences quickly. Set operators and Joins are similar in that th…
Improving on a SAS programming pattern
Earlier this week I described a common programming pattern in the SAS macro language. The pattern sets up a loop for processing each distinct value of a classification variable. The program uses the PROC SQL SELECT INTO feature to populate SAS macro variables. The effect: you can roll your own […]
Convert written numbers to Arabic numerals
In Natural Language Processing it can be helpful within a larger body of text to standardize written numbers to Arabic numerals. For example, we will change “I am forty-six years old” to “I am 46 years old,” so the age … C…
Creating a prompt for a group of data values without the administrator’s help
I have previously spoken about using custom formats and from SAS Information Maps and how they can be used to categorize data differently for your end users. The problem for some is that this requires establishing the format on the SAS server, typicall…
Take a free e-Course at SAS Global Forum
Hello! I hope you had a chance to read about e-Learning in last week’s blog. For those of you who want to see and try e-Learning, please come visit me at the e-Learning booth at SAS Global Forum in Orlando. In the weeks to come I will tell you mo…
Multicollinearity and the solutions
In his book, Rudolf Freund described a confounding phenomenon while fitting a linear regression. Given a small data set below, there are three variables – dependent variable(y) and independent variables(x1 and x2). Using x2 to fit y alone, the estimat…
Example 9.24: Changing the parameterization for categorical predictors
In our book, we discuss the important question of how to assign different parameterizations to categorical variables when fitting models (section 3.1.3). We show code in R for use in the lm() function, as follows:lm(y ~ x, contrasts=list(x,”contr.trea…