I wrote more than 100 posts for The DO Loop blog in 2017. The most popular articles were about SAS programming tips, statistical data analysis, and simulation and bootstrap methods. Here are the most popular articles from 2017 in each category. General SAS programming techniques INTCK and INTNX: Do you [...] The post The top 10 posts from <em>The DO Loop</em> in 2017 appeared first on The DO Loop.
Slice, slice, baby! You've got to slice, slice, baby! When you fit a regression model that has multiple explanatory variables, it is a challenge to effectively visualize the predicted values. This article describes how to visualize the regression model by slicing the explanatory variables. In SAS, you can use the [...] The post Visualize multivariate regression models by slicing continuous variables appeared first on The DO Loop.
Imputing missing data is the act of replacing missing data by nonmissing values. Mean imputation replaces missing data in a numerical variable by the mean value of the nonmissing values. This article shows how to perform mean imputation in SAS. It also presents three statistical drawbacks of mean imputation. How [...] The post Mean imputation in SAS appeared first on The DO Loop.
A common question on discussion forums is how to compute a principal component regression in SAS. One reason people give for wanting to run a principal component regression is that the explanatory variables in the model are highly correlated which each other, a condition known as multicollinearity. Although principal component [...] The post Principal component regression in SAS appeared first on The DO Loop.
In a large simulation study, it can be convenient to have a "control file" that contains the parameters for the study. My recent article about how to simulate multivariate normal clusters demonstrates a simple example of this technique. The simulation in that article uses an input data set that contains [...] The post Data-driven simulation appeared first on The DO Loop.
When you implement a statistical algorithm in a vector-matrix language such as SAS/IML, R, or MATLAB, you should measure the performance of your implementation, which means that you should time how long a program takes to analyze data of varying sizes and characteristics. There are some general tips that can [...] The post 6 tips for timing the performance of algorithms appeared first on The DO Loop.
The SAS analytical documentation has a new look. Beginning with the 14.2 release of the SAS analytical products (which shipped with SAS 9.4m4 in November 2016), the HTML version of the online documentation has moved to a new framework called the Help Center. The URL for the online documentation is [...] The post Five reasons to check out the new SAS analytical documentation appeared first on The DO Loop.
For SAS programmers, the PUT statement in the DATA step and the %PUT macro statement are useful statements that enable you to display the values of variables and macro variables, respectively. By default, the output appears in the SAS log. This article shares a few tips that help you to [...] The post PUT it there! Six tips for using PUT and %PUT statements in SAS appeared first on The…
Do you want to create customized SAS graphs by using PROC SGPLOT and the other ODS graphics procedures? An essential skill that you need to learn is how to merge, join, append, and concatenate SAS data sets that come from different sources. The SAS statistical graphics procedures (SG procedures) enable […] The post Append data to add markers to SAS graphs appeared first on The DO Loop.
Every year near Halloween I write an article in which I demonstrate a simple programming trick that is a real treat to use. This year's trick (which features the CMISS function and the crossproducts matrix in SAS/IML) enables you to count the number of observations that are missing for pairs […] The post Counting observations for which two events occur appeared first on The DO Loop.
