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Analytics | Learn SAS

Rick WicklinMay 12, 2025 0

Stratified bootstrapping and when to use it

When you use the bootstrap method in statistics, the most common resampling method is called case resampling. For data that has N observations, each bootstrap sample is created by sampling with replacement from the N observations (or "cases") in the data. However, if the data set includes categorical variables, it

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Analytics | Data Visualization | Programming Tips

Rick WicklinApril 21, 2025 1

Updating old SAS programs: A case study with PROC LOESS

SAS programmers love to brag that the SAS will still run a program they wrote twenty or forty years. This is both a blessing and a curse. It's a blessing because it frees the statistical programmer from needing to revisit and rewrite code that was written long ago. It's a

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Analytics | Programming Tips

Rick WicklinApril 14, 2025 0

Newton's minimization method

Isaac Newton had many amazing scientific and mathematical accomplishments. His law of universal gravitation and his creation of calculus are at the top of the list! But in the field of numerical analysis, "Newton's Method" was a groundbreaking advancement for solving for a root of a nonlinear smooth function. The

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Analytics

Rick WicklinApril 2, 2025 0

Did George Box say, "All models are wrong, but some are useful"?

Nearly every statistician has heard the aphorism, "All models are wrong, but some are useful." The quote is attributed to George Box, an early and influential thinker about statistics. Did George Box actually say this quote? Yes, he did. The first part of the quote ("All models are wrong") appeared

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Analytics | Data Visualization | Programming Tips

Rick WicklinMarch 24, 2025 0

The quantile fit plot: Comparing empirical and predicted quantiles for a univariate model

A common task in statistics is to model data by using a parametric probability distribution, such as the normal, lognormal, beta, or gamma distributions. There are many ways to assess how well the model fits the data, including graphical methods such as a Q-Q plot and formal statistical tests such

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Analytics | Programming Tips

Rick WicklinMarch 10, 2025 0

Pi to the power of pi

Happy Pi Day! Every year on March 14th (written 3/14 in the US), people in the mathematical sciences celebrate "all things pi-related" because 3.14 is the three-decimal approximation to π ≈ 3.14159265358979.... The purpose of this day is to have fun, celebrate the importance of mathematics, and maybe learn a

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Analytics | Learn SAS | Programming Tips

Rick WicklinMarch 3, 2025 0

An explicit formula for eigenvalues of an AR(1) correlation matrix

The first-order autoregressive (AR(1)) correlation structure is important for applications in time series modeling and for repeated measures analysis. The AR(1) model provides a simple situations where measurements (on the same subject) that are closer in time are correlated more strongly than measurements recorded far apart. The AR(1) model uses

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Analytics | Learn SAS

Rick WicklinFebruary 24, 2025 0

Use the EFFECTPLOT statement to visualize binomial regression models in SAS

In a binomial regression model, the response variable is the proportion of successes for a given number of trials. In SAS regression procedures, you specify a binomial model by using the EVENTS/TRIALS syntax on the MODEL statement. Many analysts use the LOGISTIC or GENMOD procedures to fit binomial models. Visualizing

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Analytics | Learn SAS | Programming Tips

Rick WicklinFebruary 17, 2025 0

Deviance residuals and the DEVIANCE function in SAS

Many people have an intuitive feel for residuals in least square models and know that the sum of squared residuals is a goodness-of-fit measure. Generalized linear regression models use a different but related idea, called deviance residuals. What are deviance residuals, and how can you compute them? Deviance residuals (and

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Analytics | Programming Tips

Rick WicklinFebruary 3, 2025 1

Use the Lambert W function to solve equations that involve exponential functions

I previously wrote an article about the Lambert W function. The Lambert W function is the inverse of the function g(x) = x exp(x). This means that you can use it to find the value of x such that g(x)=c for any value of c in the range of g, which

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