Rider University

About: Rider University is a education organization based out in Lawrenceville, New Jersey, United States. It is known for research contribution in the topics: Dosimetry & Creativity. The organization has 881 authors who have published 1934 publications receiving 50752 citations.

Why Questionable Assessment Practices Remain Popular in School Psychology: Instructional Materials as Pedagogic Vehicles:

Abstract: Surveys reveal that many school psychologists continue to employ cognitive profile analysis despite the long-standing history of negative research results from this class of practice. This begets t...

Time out of work: career costs for men and women US managers

Abstract: Purpose – This study examines the impact of employment gaps on career success for men and women managers. Women have had concerns about their ability to achieve career success in managerial careers that had required uninterrupted commitment.Design/methodology/approach – The study analyzes mail survey data collected in early post‐MBA career from men and women MBAs. Two cohorts of alumni were sent surveys containing questions on career and demographic factors. Career success was assessed using an objective measure (yearly income) and a subjective measure (career satisfaction).Findings – MBAs with employment gaps earned less than those continuously employed for both the early and recent cohorts. This income penalty appears to be worse for men. Career satisfaction is not impacted by an employment gap for the recent cohort.Research limitations/implications – Since the sample is geographically limited, the findings may not apply to other regions of the US or other countries.Practical implications – There is sti...

Demand for illicit drugs among pregnant women.

Abstract: We use postpartum survey data linked to medical records and city-level drug prices to estimate the demand for illicit drugs among pregnant women. We find that a $10 increase in the retail price of a gram of pure cocaine decreases illicit drug use by 12–15%. The estimated price effects for heroin are lower than for cocaine and are less robust across alternative model specifications. This study provides the first estimates of the effects of drug prices on prenatal drug use and yields important information about the potential of drug enforcement as a tool for reducing illicit drug use among pregnant women.

Size-growth asymmetry is not consistently related to productivity across an eastern US temperate forest network

Abstract: Modeling and forecasting forests as carbon sinks require that we understand the primary factors affecting productivity. One factor thought to be positively related to stand productivity is the degree of asymmetry, or the slope of the relationship between tree size and biomass growth. Steeper slopes indicate disproportionate productivity of big trees relative to small trees. Theoretically, big trees outcompete smaller trees during favorable growth conditions because they maintain better access to light. For this reason, high productivity forests are expected to have asymmetric growth. However, empirical studies do not consistently support this expectation, and those that do are limited in spatial or temporal scope. Here, we analyze size–growth relationships from 1970 to 2011 across a diverse network of forest sites in the eastern United States (n = 16) to test whether asymmetry is consistently related to productivity. To investigate this relationship, we analyze asymmetry-productivity relationships between our 16 forests at non-overlapping annual, 2-, 5-, 10-, and 20-year sampling intervals and find that asymmetry is negatively related to productivity, but the strength depends on the specific interval considered. Within-site temporal variability in asymmetry and productivity are generally positively correlated over time, except at the 5-year remeasurement interval. Rather than confirming or failing to support a positive relationship between asymmetry and productivity, our findings suggest caution interpreting these metrics since the relationship varies across forest types and temporal scales.

Monte Carlo Modeling of Contemporary Intelligence Test (IQ) Factor Structure: Implications for IQ Assessment, Interpretation, and Theory.

Abstract: Researchers continue to debate the constructs measured by commercial ability tests. Factor analytic investigations of these measures have been used to develop and refine widely adopted psychometric theories of intelligence particularly the Cattell-Horn-Carroll (CHC) model. Even so, this linkage may be problematic as many of these investigations examine a particular instrument in isolation and CHC model specification across tests and research teams has not been consistent. To address these concerns, the present study used Monte Carlo resampling to investigate the latent structure of four of the most widely used intelligence tests for children and adolescents. The results located the approximate existence of the publisher posited CHC theoretical group factors in the Differential Abilities Scales-Second edition and the Kaufman Assessment Battery for Children-Second edition but not in the Wechsler Intelligence Scale for Children-Fifth edition or the Woodcock-Johnson IV Tests of Cognitive Abilities. Instead, the results supported alternative conceptualizations from independent factor analytic research. Additionally, whereas a bifactor model produced superior fit indices in two instruments (Wechsler Intelligence Scale for Children-Fifth edition and Woodcock-Johnson IV Tests of Cognitive Abilities), a higher order structure was found to be superior in the Kaufman Assessment Battery for Children-Second edition and the Differential Abilities Scales-Second edition. Regardless of the model employed, the general factor captured a significant portion of each instrument's variance. Implications for IQ test assessment, interpretation, and theory are discussed.