The DO Loop

Analytics

Find out how analytics, from data mining to cognitive computing, is changing the way we do business

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

English

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

English

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

English

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

English

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

English

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

English

Analytics | Data Visualization

Rick WicklinMay 2, 2018 2

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

English

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.

English

Analytics | Programming Tips

Rick WicklinApril 25, 2018 0

An easier way to run thousands of regressions

SAS programmers on SAS discussion forums sometimes ask how to run thousands of regressions of the form Y = B0 + B1*X_i, where i=1,2,.... A similar question asks how to solve thousands of regressions of the form Y_i = B0 + B1*X for thousands of response variables. I have previously

English

Analytics | Data Visualization | Programming Tips

Euclidean and L1 distances between observations and a target value for standardized data

Rick WicklinMarch 28, 2018 3

Find the distances between observations and a target value

Suppose you want to find observations in multivariate data that are closest to a numerical target value. For example, for the students in the Sashelp.Class data set, you might want to find the students whose (Age, Height, Weight) values are closest to the triplet (13, 62, 100). The way to

English

Blogs

Blogs

Analytics