Three criticisms of conventional uses of structural significance testing are elaborated; and alternatives for augmenting statistical significance tests are reviewed, which include emphasizing effect size, evaluating statistical significance in a sample size context, and evaluating result replicability. Among ways of estimating result…

Considers problems which arise when researchers do not have the optimally large sample sizes desired in structural equation modeling. Discusses the ways in which small sample size affects assessment of model fit. Provides a new estimator that may be beneficial for use in small-sample situations. (Author/RH)

Researchers increasingly recognize that significance tests are limited in their ability to inform scientific practice. Common errors in interpreting significance tests and three strategies for augmenting the interpretation of significance test results are illustrated. The first strategy for augmenting the interpretation of significance tests…

Demonstrates that magnitude-of-effects (ME) estimates vary in susceptibility to sample-size bias depending on whether they are directional or nondirectional estimates. Also demonstrates that study characteristics that influence size of ME estimates can be explicitly taken into account when comparing studies. Emphasizes need to consider study…

Randomized response measurement techniques have been proposed to overcome subject unwillingness to answer embarrassing or threatening questions truthfully. Many of the applications to date have dealt with health-related issues. This article demonstrates the application of the unrelated question randomized response design with one such question.…

Three criticisms of overreliance on results from statistical significance tests are noted. It is suggested that: (1) statistical significance tests are often tautological; (2) some uses can involve comparisons that are not completely sensible; and (3) using statistical significance tests to evaluate both methodological assumptions (e.g., the…

There are times in survey research when missing values need to be estimated. The robustness of four variations of regression and substitution by mean methods was examined using a 3x3x4 factorial design. The regression variations included in the study were: (1) regression using a single best predictor; (2) two best predictors; (3) all available…

An issue facing researchers who study very select populations is how to obtain reliability estimates on instruments. When the populations and resulting samples are very small and select, the ability to obtain reliability estimates becomes very difficult. As a result, many researchers ignore reliability concerns and forge ahead with data…

Tracking and two statistical methods (probability weighting and sample selection modeling) were studied as ways to minimize bias attributable to sample attrition in school-based studies. Data on student smoking from 30 middle schools illustrate that sample weighting yields the best results, with estimates superior to sample selection and much less…