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Analytics | Learn SAS | Programming Tips

Rick WicklinMarch 22, 2023 2

Partial correlation: controlling for confounding variables

A data analyst wanted to estimate the correlation between two variables, but he was concerned about the influence of a confounding variable that is correlated with them. The correlation might affect the apparent relationship between main two variables in the study. A common confounding variable is age because young people

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Analytics | Learn SAS | Programming Tips

Rick WicklinMarch 15, 2023 2

Fitting a distribution to an expert's opinion: An application of the metalog distribution

Most homeowners know that large home improvement projects can take longer than you expect. Whether it's remodeling a kitchen, adding a deck, or landscaping a yard, big projects are expensive and subject to a lot of uncertainty. Factors such as weather, the availability of labor, and the supply of materials,

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Analytics | Learn SAS | Programming Tips

Rick WicklinMarch 13, 2023 1

Use the metalog distribution in SAS

A previous article describes the metalog distribution (Keelin, 2016). The metalog distribution is a flexible family of distributions that can model a wide range of shapes for data distributions. The metalog system can model bounded, semibounded, and unbounded continuous distributions. This article shows how to use the metalog distribution in

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Analytics | Programming Tips

Rick WicklinMarch 1, 2023 0

The distribution of the difference between two beta random variables

A SAS programmer wanted to compute the distribution of X-Y, where X and Y are two beta-distributed random variables. Pham-Gia and Turkkan (1993) derive a formula for the PDF of this distribution. Unfortunately, the PDF involves evaluating a two-dimensional generalized hypergeometric function, which is not available in all programming languages.

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Analytics | Programming Tips

Rick WicklinFebruary 27, 2023 0

Compute hypergeometric functions in SAS

In applied mathematics, there is a large collection of "special functions." These function appera in certain applications, often as the solution to a differential equation, but also in the definition of probability distributions. For example, I have written about Bessel functions, the complete and incomplete gamma function, and the complete

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Analytics

Rick WicklinFebruary 22, 2023 3

What is the metalog distribution?

The metalog family of distributions (Keelin, Decision Analysis, 2016) is a flexible family that can model a wide range of continuous univariate data distributions when the data-generating mechanism is unknown. This article provides an overview of the metalog distributions. A subsequent article shows how to download and use a library

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Analytics | Learn SAS | Programming Tips

Rick WicklinFebruary 20, 2023 2

Simulate from a bounded distribution that has a specified mean

A SAS programmer asked for help to simulate data from a distribution that has certain properties. The distribution must be supported on the interval [a, b] and have a specified mean, μ, where a < μ < b. It turns out that there are infinitely many distributions that satisfy these

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Analytics | Programming Tips

Rick WicklinFebruary 13, 2023 0

Estimate the pth root of a Markov transition matrix

You can use a Markov transition matrix to model the transition of an entity between a set of discrete states. A transition matrix is also called a stochastic matrix. A previous article describes how to use transition matrices for stochastic modeling. You can estimate a Markov transition matrix by using

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Analytics | Data Visualization | Learn SAS

Rick WicklinJanuary 18, 2023 0

Visualize how parameters in a binary logistic regression model affect the probability of the event

A previous article shows that you can use the Intercept parameter to control the ratio of events to nonevents in a simulation of data from a logistic regression model. If you decrease the intercept parameter, the probability of the event decreases; if you increase the intercept parameter, the probability of

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Analytics | Programming Tips

Rick WicklinJanuary 16, 2023 1

Simulate data from a logistic regression model: How the intercept parameter affects the probability of the event

This article shows that you can use the intercept parameter to control the probability of the event in a simulation study that involves a binary logistic regression model. For simplicity, I will simulate data from a logistic regression model that involves only one explanatory variable, but the main idea applies

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