Getting a "wrong" sign in empirical work is a common phenomenon. Remarkably, econometrics textbooks provide very little information to practitioners on how this problem can arise. The author exposits a long list of ways in which a wrong sign can occur and how it might be corrected.

Ignoring a level can have a substantial impact on the conclusions of a multilevel analysis. For intercept-only models and for balanced data, we derive these effects analytically. For more complex random intercept models or for unbalanced data, a simulation study is performed. Most important effects concern estimates and corresponding standard…

In mean and covariance structure analysis, the chi-square difference test is often applied to evaluate the number of factors, cross-group constraints, and other nested model comparisons. Let model M[a] be the base model within which model M[b] is nested. In practice, this test is commonly used to justify M[b] even when M[a] is misspecified. The…

Type I error rates for PARSCALE's fit statistic were examined. Data were generated to fit the partial credit or graded response model, with test lengths of 10 or 20 items. The ability distribution was simulated to be either normal or uniform. Type I error rates were inflated for the shorter test length and, for the graded-response model, also for…

Two methods, direct maximum likelihood (ML) and the expectation maximization (EM) algorithm, can be used to obtain ML parameter estimates for structural equation models with missing data (MD). Although the 2 methods frequently produce identical parameter estimates, it may be easier to satisfy missing at random assumptions using EM. However, no…

The primary purpose of this study was to examine relative performance of 2 power estimation methods in structural equation modeling. Sample size, alpha level, type of manifest variable, type of specification errors, and size of correlation between constructs were manipulated. Type 1 error rate of the model chi-square test, empirical critical…

We demonstrate a model for categorical data that parallels the MIMIC model for continuous data. The model is equivalent to a latent class model with observed covariates; further, it includes simple handling of missing data. The model is used on data from a large-scale study of HIV that had both biological measures of infection and self-report…

In this article, the authors (a) illustrate how displaying disattenuated correlation coefficients alongside their unadjusted counterparts will allow researchers to assess the impact of unreliability on bivariate relationships and (b) demonstrate how a proposed new "what if reliability" analysis can complement null hypothesis significance…

"Little by little, the child develops," wrote an undergraduate in a friend's cognitive development class, and so, for the most part, it is. But what explains the U's of cognitive development? Namy, Campbell, and Tomasello and Cashon and Cohen take a standard approach to understanding U-shaped curves: as the product of a mix of different cognitive…

Retrospective or post hoc power analysis is recommended by reviewers and editors of many journals. Little literature has been found that gave a serious study of the post hoc power. When the sample size is large, the observed effect size is a good estimator of the true power. This article studies whether such a power estimator provides valuable…

The correction for attenuation due to measurement error (CAME) has received many historical criticisms, most of which can be traced to the limited ability to use CAME inferentially. Past attempts to determine confidence intervals for CAME are summarized and their limitations discussed. The author suggests that inference requires confidence sets…

Test reliability is a concept central to classical test theory and it is commonly stated as a requirement that a test attain a certain level of reliability before it be considered of sufficient quality for practical use. This article discusses the role of reliability in item response theory, and in particular the role of reliability in contexts…

This study applied kernel equating (KE) in two scenarios: equating to a very similar population and equating to a very different population, referred to as a distant population, using SAT® data. The KE results were compared to the results obtained from analogous classical equating methods in both scenarios. The results indicate that KE results are…

Two versions of a general method for approximating standard error of regression effect estimates within an IRT-based latent regression model are compared. The general method is based on Binder's (1983) approach, accounting for complex samples and finite populations by Taylor series linearization. In contrast, the current National Assessment of…

Traditionally, the fixed-length linear paper-and-pencil (P&P) mode of administration has been the standard method of test delivery. With the advancement of technology, however, the popularity of administering tests using adaptive methods like computerized adaptive testing (CAT) and multistage testing (MST) has grown in the field of measurement…