On Standardized Measurement in Behavioral Science.

That standardized measurement procedures are a sine qua non of "good" science is generally not questioned. Here we examine the meaning and use of standardized measurement in behavioral science. Procedures and methods of measurement that have served the physical sciences so well should not blindly be assumed to work in the same manner and with the same effectiveness in behavioral science.

Entropy Fit Indices: New Fit Measures for Assessing the Structure and Dimensionality of Multiple Latent Variables.

The accurate identification of the content and number of latent factors underlying multivariate data is an important endeavor in many areas of Psychology and related fields. Recently, a new dimensionality assessment technique based on network psychometrics was proposed (Exploratory Graph Analysis, EGA), but a measure to check the fit of the dimensionality structure to the data estimated via EGA is still lacking. Although traditional factor-analytic fit measures are widespread, recent research has identified limitations for their effectiveness in categorical variables.

Some Behaviorial Science Measurement Concerns and Proposals.

Primarily from a measurement standpoint, we question some basic beliefs and procedures characterizing the scientific study of human behavior. The relations between observed and unobserved variables are key to an empirical approach to building explanatory theories and we are especially concerned about how the former are used as proxies for the latter. We believe that behavioral science can profitably reconsider the prevailing version of this arrangement because of its vulnerability to limiting idiosyncratic aspects of observed/unobserved variable relations.

A Rejoinder.

Three commentaries on the Nesselroade and Molenaar target article in this issue are responded to in the interest of elaborating and defending the points of view expressed in our article. The commentaries feature philosophy of science, general structural modeling, and broad behavioral research perspectives. Responding to the commentaries afforded us the opportunity to clarify further matters that we deem critical to the fundamental matter of measurement in behavioral science, especially as it emphasizes (properly, we believe) the individual as the primary unit of analysis.

Test Reliability at the Individual Level.

Reliability has a long history as one of the key psychometric properties of a test. However, a given test might not measure people equally reliably. Test scores from some individuals may have considerably greater error than others.