Start-ups and other entrepreneurial ventures make a significant contribution to the US economy, particularly in the tech sector, where they comprise some of the largest and most influential companies. Yet for every high-profile, high-growth company like Apple, Facebook, Microsoft, and Google,...

Quantitative industrial relations research frequently relies on data collected from large surveys of establishments that use complex sampling designs, such as stratified and unequal probability sampling. The authors analyze two complex surveys of establishments, the National Organizations Survey...

In many surveys, the data comprise a large number of categorical variables that suffer from item nonresponse. Standard methods for multiple imputation, like log-linear models or sequential regression imputation, can fail to capture complex dependencies and can be difficult to implement...

Investigators often change how variables are measured during the middle of data-collection, for example, in hopes of obtaining greater accuracy or reducing costs. The resulting data comprise sets of observations measured on two (or more) different scales, which complicates interpretation and can...

Many statistical agencies, survey organizations, and research centers collect data that suffer from item nonresponse and erroneous or inconsistent values. These data may be required to satisfy linear constraints, for example, bounds on individual variables and inequalities for ratios or sums of...

When some of the records used to estimate the imputation models in multiple imputation are not used or available for analysis, the usual multiple imputation variance estimator has positive bias. We present an alternative approach that enables unbiased estimation of variances and, hence,...