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 . 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...