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Rick WicklinJune 27, 2018 2

Reduced models: A way to choose initial parameters for a mixed model

This article describes how to obtain an initial guess for nonlinear regression models, especially nonlinear mixed models. The technique is to first fit a simpler fixed-effects model by replacing the random effects with their expected values. The parameter estimates for the fixed-effects model are often good initial guesses for the

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Analytics

Rick WicklinJune 25, 2018 4

Use a grid search to find initial parameter values for regression models in SAS

When you fit nonlinear fixed-effect or mixed models, it is difficult to guess the model parameters that fit the data. Yet, most nonlinear regression procedures (such as PROC NLIN and PROC NLMIXED in SAS) require that you provide a good guess! If your guess is not good, the fitting algorithm,

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Analytics | Programming Tips

Rick WicklinJune 20, 2018 11

The bootstrap method in SAS: A t test example

A previous article provides an example of using the BOOTSTRAP statement in PROC TTEST to compute bootstrap estimates of statistics in a two-sample t test. The BOOTSTRAP statement is new in SAS/STAT 14.3 (SAS 9.4M5). However, you can perform the same bootstrap analysis in earlier releases of SAS by using

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Analytics | Learn SAS

Rick WicklinJune 18, 2018 1

The BOOTSTRAP statement for t tests in SAS

Bootstrap resampling is a powerful way to estimate the standard error for a statistic without making any parametric assumptions about its sampling distribution. The bootstrap method is often implemented by using a sequence of calls to resample from the data, compute a statistic on each sample, and analyze the bootstrap

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Analytics | Data Visualization

Rick WicklinMay 31, 2018 5

Use a fringe plot to visualize binary data in logistic models

A previous article showed how to use a calibration plot to visualize the goodness-of-fit for a logistic regression model. It is common to overlay a scatter plot of the binary response on a predicted probability plot (below, left) and on a calibration plot (below, right): The SAS program that creates

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Analytics | Data Visualization

Decile calibration curve for a misspecified logistic regression model

Rick WicklinMay 16, 2018 14

Decile calibration plots in SAS

In my article about how to construct calibration plots for logistic regression models in SAS, I mentioned that there are several popular variations of the calibration plot. The previous article showed how to construct a loess-based calibration curve. Austin and Steyerberg (2013) recommend the loess-based curve on the basis of

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Analytics | Data Visualization

Calibration plot for a misspecified logistic model

Rick WicklinMay 14, 2018 16

Calibration plots in SAS

A logistic regression model is a way to predict the probability of a binary response based on values of explanatory variables. It is important to be able to assess the accuracy of a predictive model. This article shows how to construct a calibration plot in SAS. A calibration plot is

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Analytics | Programming Tips

Rick WicklinMay 9, 2018 0

Independent streams of random numbers in SAS

In a previous blog post, I discussed ways to produce statistically independent samples from a random number generator (RNG). The best way is to generate all samples from one stream. However, if your program uses two or more SAS DATA steps to simulate the data, you cannot use the same

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Analytics | Data Visualization

Rick WicklinMay 2, 2018 4

Order variables in a heat map or scatter plot matrix

Order matters. When you create a graph that has a categorical axis (such as a bar chart), it is important to consider the order in which the categories appear. Most software defaults to alphabetical order, which typically gives no insight into how the categories relate to each other. Alphabetical order

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Analytics | Data Visualization

Rick WicklinApril 30, 2018 4

Assign colors in heat maps: A study of married couples and college majors

Some say that opposites attract. Others say that birds of a feather flock together. Which is it? Phillip N. Cohen, a professor of sociology at the University of Maryland, recently posted an interesting visualization that indicates that married couples who are college graduates tend to be birds of a feather.

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