Economists often estimate models with a log-transformed dependent variable. The results from the log-transformed model are often retransformed back to the unlogged scale. Other studies have shown how to obtain consistent estimates on the original scale but have not provided variance equations for those estimates. In this paper, we derive the variance for three estimates--the conditional mean of...

In empirical work in economics it is common to report standard errors that account for clustering of units. Typically, the motivation given for the clustering adjustments is that unobserved components in outcomes for units within clusters are correlated. However, because correlation may occur across more than one dimension, this motivation makes it difficult to justify why researchers use clust...

BACKGROUND Bar code technology has decreased transcription errors in many healthcare applications. However, we have found that linear bar code identification methods are not failsafe. In this study, we sought to identify the sources of bar code decoding errors that generated incorrect patient identifiers when bar codes were scanned for point-of-care glucose testing and to develop solutions to p...

In this paper we discuss the properties of confidence intervals for regression parameters based on robust standard errors. We discuss the motivation for a modification suggested by Bell and McCaffrey (2002) to improve the finite sample properties of the confidence intervals based on the conventional robust standard errors. We show that the Bell-McCaffrey modification is a natural extension of a...

Two procedures are proposed for calculating standard errors for network statistics. Both are based on resampling of vertices: the first follows the bootstrap approach, the second the jackknife approach. In addition, we demonstrate how to use these estimated standard errors to compare statistics using an approximate t-test and how statistics can also be compared by another bootstrap approach tha...

Non-spherical errors, namely heteroscedasticity, serial correlation and crosssectional correlation are commonly present within panel data sets. These can cause significant problems for econometric analyses. The FGLS(Parks) estimator has been demonstrated to produce considerable efficiency gains in these settings. However, it suffers from underestimation of coefficient standard errors, oftentime...

This paper derives consistent standard errors for a panel Tobit model in the presence of correlated errors. The problem is framed in the context of Newey and West (1987), considering the Tobit model as a special case of a GMM estimator. JEL codes: C23, C24

Time-series–cross-section (TSCS) data are characterized by having repeated observations over time on some set of units, such as states or nations. TSCS data typically display both contemporaneous correlation across units and unit level heteroskedasity making inference from standard errors produced by ordinary least squares incorrect. Panel-corrected standard errors (PCSE) account for these thes...

The asymptotic standard errors of the IRT equating coefficients given by the mean/sigma, mean/mean and mean/geometric mean methods are derived when the two-parameter logistic model holds and item parameters are obtained by the marginal maximum likelihood estimation. The case of two nonequivalent examinee-groups and the case of single group are considered. The numerical examples show that the me...

Point process models such as the Epidemic-type Aftershock Sequence (ETAS) model have been widely used in the analysis and description of seismic catalogs and in shortterm earthquake forecasting. The standard errors of parameter estimates in the ETAS model are significant and cannot be ignored. This paper uses simulations to explore the accuracy of conventional standard error estimates based on ...