Doctoral training in statistics, measurement, and methodology in psychology: Replication and extension of Aiken, West, Sechrest, and Reno's (1990) survey of PhD programs in North America.

Abstract

In a survey of all PhD programs in psychology in the United States and Canada, the authors documented the quantitative methodology curriculum (statistics, measurement, and research design) to examine the extent to which innovations in quantitative methodology have diffused into the training of PhDs in psychology. In all, 201 psychology PhD programs (86%) participated. This survey replicated and extended a previous survey (L. S. Aiken, S. G. West, L. B. Sechrest,& R. R. Reno, 1990), permitting examination of curriculum development. Most training supported laboratory and not field research. The median of 1.6 years of training in statistics and measurement was mainly devoted to the modally 1-year introductory statistics course, leaving little room for advanced study. Curricular enhancements were noted in statistics and to a minor degree in measurement. Additional coverage of both fundamental and innovative quantitative methodology is needed. The research design curriculum has largely stagnated, a cause for great concern. Elite programs showed no overall advantage in quantitative training. Forces that support curricular innovation are characterized. Human capital challenges to quantitative training, including recruiting and supporting young quantitative faculty, are discussed. Steps must be taken to bring innovations in quantitative methodology into the curriculum of PhD programs in psychology.

What makes articles highly cited?

“…As others have mentioned repeatedly, doctoral students must be better trained in statistics (Aiken, West, & Millsap, 2008;Antonakis, et al, 2010;Steiger, 2001). In particular, authors as well as reviewers and editors must learn to "lift the hood" of statistical engines to better understand what assumptions and restrictions estimators make so that researchers do not violate these assumptions and hence bias estimates due to endogeneity or other factors.…”

An Ounce of Prevention Is Worth a Pound of Cure: Improving Research Quality Before Data Collection

“…This is a seemingly more radical recommendation given the emphasis on NHST in most doctoral-level programs (e.g., Aiken et al 2008) and the newness of the Bayesian approach in the organizational sciences. In fact, Kruschke et al (2012) content analyzed more than 10,000 articles published in 15 organizational science journals from January 2001 to December 2010 and reported that only 42 used Bayesian methods.…”

“…Yet another possible reason for the overemphasis on data analysis is that the methodological training of future scholars emphasizes data analysis over design (Tett et al 2013). In fact, very few doctoral-level courses address design by itself-a situation that has not changed much over the past three decades (Aiken et al 1990(Aiken et al , 2008). The precise reasons for the lack of relative attention to design and measurement issues are not known.…”

¿Es el final del alfa de Cronbach?

“…Su propuesta causó tal impacto que una reciente búsqueda (realizado por el autor de esta carta) a través de Google Académico® confirma que ha sido citado 35915 veces. Una de las explicaciones tentativas de la masificación del α radica en su facilidad para ser calculado mediante programas estadísticos de extensa popularidad; la ausencia de cursos de postgrado que profundicen acerca de diferentes formas de analizar la fiabilidad (Aiken, West y Millsap, 2008) y el que los asesores de tesis o editores de revista aun no estén familiarizados con otros estimadores de fiabilidad (Cho y Kim, 2015).…”