Allison (1999) notes that comparisons of logit and probit coefficients across groups can be invalid and misleading, proposes a procedure by which these problems can be corrected, and argues that ``routine use [of this method] seems advisable'' and that ``it is hard to see how [the method] can be...

Structural equation models with latent variables have been popular in the social sciences for some time. Recently such models have been used to make comparisons between groups, within dyads, and across time. However, possible problems with establishing meaningful metrics for unobservable...

Evaluative bibliometrics is concerned with comparing research units by using statistical procedures. According to Williams (2012) an empirical study should be concerned with the substantive and practical significance of the findings as well as the sign and statistical significance of effects. In...

Top-down stress testing is one way of assessing the resilience of the financial system to the risks it might face now or in the future. The Risk Assessment Model of Systemic Institutions (RAMSI) developed at the Bank of England is an example of a top-down stress-testing model and is part of the...

In this talk, we will show how to use simulations in Stata to explore to what extent and under what circumstances a test is problematic. We will illustrate this for a set of tests of the parallel regression assumption in ordered logit and probit models: the Brant, likelihood ratio, Wald, score,...

As Long & Freese show, it can often be helpful to compute predicted/expected values for hypothetical or prototypical cases. Stata 11 introduced new tools for making such calculations – factor variables and the margins command. These can do many of the things that were previously done by...

The UK economy has begun to recover over the past year but households’ financial positions remain under strain. Elevated unemployment, weak earnings growth and restricted credit availability still pose a problem for some households. But the low level of Bank Rate has continued to bear down on...

When a binary or ordinal regression model incorrectly assumes that er- ror variances are the same for all cases, the standard errors are wrong and (unlike ordinary least squares regression) the parameter estimates are biased. Hetero- geneous choice models (also known as location–scale models...

The new book by Hamilton (2004) is reviewed.