Blog Archives

Example 10.5: Convert a character-valued categorical variable to numeric

October 8, 2012
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Example 10.5: Convert a character-valued categorical variable to numeric

In some settings it may be necessary to recode a categorical variable with character values into a variable with numeric values. For example, the matching macro we discussed in example 7.35 will only match on numeric variables. One way to conve...

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Example 10.4: Multiple comparisons and confidence limits

October 1, 2012
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Example 10.4: Multiple comparisons and confidence limits

A colleague is a devotee of confidence intervals. To him, the CI have the magical property that they are immune to the multiple comparison problem-- in other words, he feels its OK to look at a bunch of 95% CI and focus on the ones that appear to exclude the null. This though...

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Example 10.3: Enhanced scatterplot with marginal histograms

September 24, 2012
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Example 10.3: Enhanced scatterplot with marginal histograms

Back in example 8.41 we showed how to make a graphic combining a scatterplot with histograms of each variable. A commenter suggested we change the R graphic to allow post-hoc plotting of, for example, lowess lines. In addition, there are further refinements to be made. In this R-only entry, we'll make the figure...

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Example 10.2: Custom graphic layouts

September 17, 2012
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Example 10.2: Custom graphic layouts

In example 10.1 we introduced data from a CPAP machine. In brief, it's hard to tell exactly what's being recorded in the data set, but it seems to be related to the pattern of breathing. Measurements are taken five times a second, leading to on the o...

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Example 10.1: Read a file byte by byte

September 10, 2012
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Example 10.1: Read a file byte by byte

More and more makers of electronic devices use standard storage media to record data. Sometimes this is central to the device's function, as in a camera, so that the data must be easy to recover. Other times, it's effectively incidental, and the device maker may not provide easy access to the stored data....

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Third year wrap-up

July 23, 2012
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Third year wrap-up

July marks the end of three years of blogging for us. By our count, we've posted 121 examples across the first three years. We aim to be helpful and interesting.As always, it's hard to get a sense of our readership. At the time we wrote this, Feedbur...

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Citing R or SAS

July 2, 2012
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Citing R or SAS

One of us recently read a colleague's first draft of a paper, in which she had written: "All analyses were done in R 2.14.0." We assume we're preaching to the converted here, when we say that the enormous amount of work that goes into R needs to be re...

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Example 9.36: Levene’s test for equal variances

June 25, 2012
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Example 9.36: Levene’s test for equal variances

The assumption of equal variances among the groups in analysis of variance is an expression of the assumption of homoscedasticity for linear models more generally. For ANOVA, this assumption can be tested via Levene's test. The test is a function of the residuals and means within each group, though various modifications are used, including the Brown-Forsythe...

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Example 9.35: Discrete randomization and formatted output

June 18, 2012
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Example 9.35: Discrete randomization and formatted output

A colleague asked for help with randomly choosing a kid within a family. This is for a trial in which families are recruited at well-child visits, but in each family only one of the children having a well-child visit that day can be in the study. The idea is that after recruiting the family, the research assistant...

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Example 9.34: Bland-Altman type plot

June 5, 2012
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Example 9.34: Bland-Altman type plot

The Bland-Altman plot is a visual aid for assessing differences between two ways of measuring something. For example, one might compare two scales this way, or two devices for measuring particulate matter. The plot simply displays the difference between the measures against their average. Rather than a statistical test, it is intended...

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