Blog Archives

Example 9.7: New stuff in SAS 9.3– Frailty models

September 27, 2011
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Example 9.7: New stuff in SAS 9.3– Frailty models

Shared frailty models are a way of allowing correlated observations into proportional hazards models. Briefly, instead of l_i(t) = l_0(t)e^(x_iB), we allow l_ij(t) = l_0(t)e^(x_ijB + g_i), where observations j are in clusters i, g_i is typically norma...

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Example 9.6: Model comparison plots (Completed)

September 21, 2011
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Example 9.6: Model comparison plots (Completed)

We often work in settings where the data set has a lot of missing data-- some missingness in the (many) covariates, some in the main exposure of interest, and still more in the outcome. (Nick describes this as "job security for statisticians").Some ana...

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Example 9.5: New stuff in SAS 9.3– proc FMM

September 13, 2011
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Example 9.5: New stuff in SAS 9.3– proc FMM

Finite mixture models (FMMs) can be used in settings where some unmeasured classification separates the observed data into groups with different exposure/outcome relationships. One familiar example of this is a zero-inflated model, where some observat...

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Example 9.4: New stuff in SAS 9.3– MI FCS

September 6, 2011
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Example 9.4: New stuff in SAS 9.3– MI FCS

We begin the new academic year with a series of entries exploring new capabilities of SAS 9.3, and some functionality we haven't previously written about.We'll begin with multiple imputation. Here, SAS has previously been limited to multivariate norma...

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Taking August off!

July 31, 2011
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Taking August off!

We'll be back with recharged batteries and lots of new entries in September. Have a great summer*!As usual, please send any questions you have about using SAS or R.*Not valid in the southern hemisphere.

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Really useful R package: sas7bdat

July 25, 2011
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Really useful R package: sas7bdat

For SAS users, one hassle in trying things in R, let alone migrating, is the difficulty of getting data out of SAS and into R. In our book (section 1.2.2) and in a blog entry we've covered getting data out of SAS native data sets. Unfortunately, for ...

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Example 9.2: Transparency and bivariate KDE

July 11, 2011
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Example 9.2:  Transparency and bivariate KDE

In Example 9.1, we showed a binning approach to plotting bivariate relationships in a large data set. Here we show more sophisticated approaches: transparent overplotting and formal two-dimensional kernel density estimation. We use the 10,000 simulat...

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A third year of entries!

July 1, 2011
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A third year of entries!

Contrary to previous reports, we started blogging after our book was published, with the conceit that we were adding examples to the book. Today marks the second anniversary of the book's appearance and of the blog. To celebrate, we're turning over o...

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Example 8.41: Scatterplot with marginal histograms

June 20, 2011
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Example 8.41: Scatterplot with marginal histograms

The scatterplot is one of the most ubiquitous, and useful graphics. It's also very basic. One of its shortcomings is that it can hide important aspects of the marginal distributions of the two variables. To address this weakness, you can add a histo...

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Example 8.40: Side-by-side histograms

June 13, 2011
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Example 8.40: Side-by-side histograms

It's often useful to compare histograms for some key variable, stratified by levels of some other variable. There are several ways to display something like this. The simplest may be to plot the two histograms in separate panels.SASIn SAS, the most d...

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