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Rick WicklinJanuary 16, 2019 10

A quantile-quantile plot (Q-Q plot) is a graphical tool that compares a data distribution and a specified probability distribution. If the points in a Q-Q plot appear to fall on a straight line, that is evidence that the data can be approximately modeled by the target distribution. Although it is

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Analytics | Data Visualization | Programming Tips

Process flow diagram shows how to resample data to create a bootstrap distribution.

Rick WicklinJanuary 9, 2019 0

10 posts from 2018 that deserve a second look

Numbers don't lie, but sometimes they don't reveal the full story. Last week I wrote about the most popular articles from The DO Loop in 2018. The popular articles are inevitably about elementary topics in SAS programming or statistics because those topics have broad appeal. However, I also write about

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Analytics | Programming Tips

Rick WicklinJanuary 7, 2019 34

Deming regression for comparing different measurement methods

Deming regression (also called errors-in-variables regression) is a total regression method that fits a regression line when the measurements of both the explanatory variable (X) and the response variable (Y) are assumed to be subject to normally distributed errors. Recall that in ordinary least squares regression, the explanatory variable (X)

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Learn SAS | Programming Tips

Calibration plot for a misspecified logistic model

Rick WicklinJanuary 2, 2019 2

Top posts from The DO Loop in 2018

Last year, I wrote more than 100 posts for The DO Loop blog. Of these, the most popular articles were about data visualization, SAS programming tips, and statistical data analysis. Here are the most popular articles from 2018 in each category. Data Visualization Visualize repetition in song lyrics: In one

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Analytics | Learn SAS | Programming Tips

Rick WicklinDecember 12, 2018 7

The essential guide to bootstrapping in SAS

This article describes best practices and techniques that every data analyst should know before bootstrapping in SAS. The bootstrap method is a powerful statistical technique, but it can be a challenge to implement it efficiently. An inefficient bootstrap program can take hours to run, whereas a well-written program can give

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Learn SAS | Programming Tips

Rick WicklinDecember 5, 2018 1

When is a histogram not a histogram? When it's a table!

Recently a SAS programmer wanted to obtain a table of counts that was based on a histogram. I showed him how you can use the OUTHIST= option on the HISTOGRAM statement in PROC UNIVARIATE to obtain that information. For example, the following call to PROC UNIVARIATE creates a histogram for

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Programming Tips

Rick WicklinNovember 28, 2018 11

Singular parameterizations, generalized inverses, and regression estimates

I remember the first time I used PROC GLM in SAS to include a classification effect in a regression model. I thought I had done something wrong because the parameter estimates table was followed by a scary-looking note: Note: The X'X matrix has been found to be singular, and a

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Learn SAS | Programming Tips

Rick WicklinNovember 19, 2018 2

Select ODS tables by using wildcards and regular expressions in SAS

You might know that you can use the ODS SELECT statement to display only some of the tables and graphs that are created by a SAS procedure. But did you know that you can use a WHERE clause on the ODS SELECT statement to display tables that match a pattern?

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Analytics | Data Visualization | Programming Tips

Rick WicklinNovember 14, 2018 13

Create and compare ROC curves for any predictive model

An ROC curve graphically summarizes the tradeoff between true positives and true negatives for a rule or model that predicts a binary response variable. An ROC curve is a parametric curve that is constructed by varying the cutpoint value at which estimated probabilities are considered to predict the binary event.

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Programming Tips

Rick WicklinNovember 7, 2018 1

Visualize the feasible region for a constrained optimization

When solving optimization problems, it is harder to specify a constrained optimization than an unconstrained one. A constrained optimization requires that you specify multiple constraints. One little typo or a missing minus sign can result in an infeasible problem or a solution that is unrelated to the true problem. This

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