Many latent traits in social sciences display a hierarchical structure, such as intelligence, cognitive ability, or personality. Usually a second-order factor is linearly related to a group of first-order factors (also called domain abilities in cognitive ability measures), and the first-order...

The item response times (RTs) collected from computerized testing represent an underutilized type of information about items and examinees. In addition to knowing the examinees’ responses to each item, we can investigate the amount of time examinees spend on each item. Current models for RTs...

This paper applies a Bayesian dynamic factor model to analyze the co-movement of government debt and economic growth in 12 euro-area countries from 1970--2009. We decompose the variations in output growth and government debt into three distinct factors: (i) a common factor capturing co-movement...

Traditional methods for item selection in computerized adaptive testing only focus on item information without taking into consideration the time required to answer an item. As a result, some examinees may receive a set of items that take a very long time to finish, and information is not...

For effective planning, design, and management of water resources engineering, the probability distribution of annual streamflow is necessary. The method of L-moments is applied to identify the probability distribution type of annual streamflow in different climatic regions of Canada. In the...

This paper shows that an unobserved common factor drives the co-movement of government debt in the euro area. The old-age dependency ratio explains the factor after controlling for the Maastricht Treaty, the adoption of the euro, and the ongoing crisis.

With the advent of web-based technology, online testing is becoming a mainstream mode in large-scale educational assessments. Most online tests are administered continuously in a testing window, which may post test security problems because examinees who take the test earlier may share...

This article proposes to use the computer-based bootstraptechnique to test the significance of the lag-k sampleserial correlation coefficient (r <Subscript>k</Subscript>) of a time series.The bootstrap approach is free of sample distribution types, freeof restrictive assumptions, and easy to understand and implement....</subscript>