While both SAS and R are powerful systems for statistical analysis, they can be frustrating to new users or those learning statistics for the first time. RThe mosaic package is designed to help simplify the interface for such new users, while allowing ...

SAS and R often provide different levels of details from output. This is particularly true for the descriptive analysis of contingency tables, where SAS makes it easy to display tables with additional quantities (such as the observed cell count).The m...

Scatterplots can get very hard to interpret when displaying large datasets, as points inevitably overplot and can't be individually discerned. A number of approaches have been crafted to help with this problem. One approach uses binning. This approa...

While skewness and kurtosis are not as often calculated and reported as mean and standard deviation, they can be useful at times. Skewness is the 3rd moment around the mean, and characterizes whether the distribution is symmetric (skewness=0). Kurtos...

We've been impressed with how helpful the CRAN Task Views are in guiding us in R as we wend our way through the huge number of add-on packages (3021 as of May, 2011). These are web pages that are maintained by volunteers with expertise in a specified ...

In our last entry, we described reading Excel files. In this entry, we do the opposite: write native Excel files.RIn R, the WriteXLS package provides this functionality. It uses perl to do the heavy lifting, and the main complication is to install th...

R objects that reside in other R objects can require a lot of typing to access. For example, to refer to a variable x in a dataframe df, one could type df$x. This is no problem when the dataframe and variable names are short, but can become burdensom...

We often simulate data in SAS or R to confirm analytical results. For example, consider the following problem from the excellent text by Rice:Let U1, U2, and U3 be independent random variables uniform on [0, 1]. What is the probability that the roots...

Tim Hesterberg has effectively argued for a larger role for resampling based inference in introductory statistics courses (and statistical practice more generally). While the Central Limit Theorem is a glorious result, and the Student t-test remarkabl...

It's been a long winter so far in New England, with many a snow storm. In this entry, we consider a simulation to complement the analytic solution for a probability problem concerning snow. Consider a company that buys a policy to insure its revenue ...

A more or less anonymous reader commented on our last post, where we were reading data from a file with a varying number of fields. The format of the file was:1 Las Vegas, NV --- 53.3 --- --- 12 Sacramento, CA --- 42.3 --- --- 2The complication in the...

A student came with a question about how to snag data from a PDF report for analysis. Once she'd copied things her text file looked like:1 Las Vegas, NV --- 53.3 --- --- 12 Sacramento, CA --- 42.3 --- --- 23 Miami, FL --- 41.8 --- --- 34 Tucson, AZ --...

In recent entries (here, here, here and here), we've been fitting a series of latent class models using SAS and R. One of the most commonly used and powerful package for latent class model estimation is Mplus. In this entry, we demonstrate how to use...

In recent entries (here, here, and here), we've been fitting a series of latent class models using SAS and R. One of the most commonly used and powerful software package for latent class model estimation is Mplus. This commercial software includes su...

In Example 8.21 we described how to fit a latent class model to data from the HELP dataset using SAS and R (using poLCA(), and then followed up in example 8.22 using randomLCA(). In both entries, we classified subjects based on their observed (manifes...

In Example 8.21 we described how to fit a latent class model to data from the HELP dataset using SAS and R. Subjects were classified based on their observed (manifest) status on the following variables (on street or in shelter in past 180 days [homele...

Latent class analysis is a technique used to classify observations based on patterns of categorical responses. Collins and Lanza's book,"Latent Class and Latent Transition Analysis," provides a readable introduction, while the UCLA ATS center has an o...

In section 1.11.4 (p. 50), we discuss referring to lists of variables in a data set. In SAS, this can be done for variable stored in adjacent columns with the "var_x -- var_y" syntax and for variables with sequentially enumerated suffixes with the "va...

Last week we made an impassioned plea for attention to style in formatting R and SAS code.While it's always better to adopt a consistent style and use it whenever you write code, the reality is that sometimes formatting slips (or you end up repurposing...

As we get close to the end of the year, it's time to look back over the past year and think of resolutions for 2011 and beyond. One that's often on my mind relates to ways to structure my code to make it clearer to others (as well as to myself ...