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Principal component regression in SAS: Loadings plot

Rick WicklinOctober 25, 2017 2

Should you use principal component regression?

This article describes the advantages and disadvantages of principal component regression (PCR). This article also presents alternative techniques to PCR. In a previous article, I showed how to compute a principal component regression in SAS. Recall that principal component regression is a technique for handling near collinearities among the regression

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Analytics | Learn SAS

Rick WicklinOctober 23, 2017 6

Principal component regression in SAS

A common question on discussion forums is how to compute a principal component regression in SAS. One reason people give for wanting to run a principal component regression is that the explanatory variables in the model are highly correlated which each other, a condition known as multicollinearity. Although principal component

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Analytics | Learn SAS

Diffogram for multiple comparisons of means in SAS

Rick WicklinOctober 18, 2017 8

The diffogram and other graphs for multiple comparisons of means

In a previous article, I discussed the lines plot for multiple comparisons of means. Another graph that is frequently used for multiple comparisons is the diffogram, which indicates whether the pairwise differences between means of groups are statistically significant. This article discusses how to interpret a diffogram. Two related plots

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Analytics | Data Visualization | Learn SAS

Lines plot for multiple comparison of means in SAS

Rick WicklinOctober 16, 2017 13

Graphs for multiple comparisons of means: The lines plot

Last week Warren Kuhfeld wrote about a graph called the "lines plot" that is produced by SAS/STAT procedures in SAS 9.4M5. (Notice that the "lines plot" has an 's'; it is not a line plot!) The lines plot is produced as part of an analysis that performs multiple comparisons of

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Analytics | Data Visualization | Learn SAS

Rick WicklinOctober 4, 2017 1

Create and interpret a weighted histogram

If you perform a weighted statistical analysis, it can be useful to produce a statistical graph that also incorporates the weights. This article shows how to construct and interpret a weighted histogram in SAS. How to construct a weighted histogram Before constructing a weighted histogram, let's review the construction of

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Analytics | Learn SAS

Visualization of regression that uses a weight variable in SAS

Rick WicklinOctober 2, 2017 61

How to understand weight variables in statistical analyses

How can you specify weights for a statistical analysis? Hmmm, that's a "weighty" question! Many people on discussion forums ask "What is a weight variable?" and "How do you choose a weight for each observation?" This article gives a brief overview of weight variables in statistics and includes examples of

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Analytics | Programming Tips

Rick WicklinSeptember 25, 2017 6

Simulate multivariate normal data in SAS by using PROC SIMNORMAL

My article about Fisher's transformation of the Pearson correlation contained a simulation. The simulation uses the RANDNORMAL function in SAS/IML software to simulate multivariate normal data. If you are a SAS programmer who does not have access to SAS/IML software, you can use the SIMNORMAL procedure in SAS/STAT software to

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Analytics | Learn SAS

Rick WicklinSeptember 20, 2017 17

Fisher's transformation of the correlation coefficient

Pearson's correlation measures the linear association between two variables. Because the correlation is bounded between [-1, 1], the sampling distribution for highly correlated variables is highly skewed. Even for bivariate normal data, the skewness makes it challenging to estimate confidence intervals for the correlation, to run one-sample hypothesis tests ("Is

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Analytics | Programming Tips

Rick WicklinSeptember 11, 2017 1

Symbolic derivatives in SAS

Did you know that you can get SAS to compute symbolic (analytical) derivatives of simple functions, including applying the product rule, quotient rule, and chain rule? SAS can form the symbolic derivatives of single-variable functions and partial derivatives of multivariable functions. Furthermore, the derivatives are output in a form that

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Analytics

Rick WicklinSeptember 5, 2017 4

7 ways to view correlation

Correlation is a fundamental statistical concept that measures the linear association between two variables. There are multiple ways to think about correlation: geometrically, algebraically, with matrices, with vectors, with regression, and more. To paraphrase the great songwriter Paul Simon, there must be 50 ways to view your correlation! But don't

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