Steven Andrew Culpepper

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Cross-level interaction effects lie at the heart of multilevel contingency and interactionism theories. Researchers have often lamented the difficulty of finding hypothesized cross-level interactions, and to date there has been no means by which the statistical power of such tests can be evaluated. We develop such a method and report results of a(More)
We developed a new analytic proof and conducted Monte Carlo simulations to assess the effects of methodological and statistical artifacts on the relative accuracy of intercept- and slope-based test bias assessment. The main simulation design included 3,185,000 unique combinations of a wide range of values for true intercept- and slope-based test bias, total(More)
We tested competing hypotheses, based on learning and job burnout theories as well as autobiographical case studies, regarding the careerwide research productivity of 58 past editors of six journals over a 50-year period (i.e., approximately mid-1950s to mid-2000s). fluctuations in the research productivity of editors such that, on average, their research(More)
Statistical prediction remains an important tool for decisions in a variety of disciplines. An equally important issue is identifying factors that contribute to more or less accurate predictions. The time series literature includes well developed methods for studying predictability and volatility over time. This article develops distribution-appropriate(More)
Analysis of covariance (ANCOVA) is used widely in psychological research implementing nonexperimental designs. However, when covariates are fallible (i.e., measured with error), which is the norm, researchers must choose from among 3 inadequate courses of action: (a) know that the assumption that covariates are perfectly reliable is violated but use ANCOVA(More)
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