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.

An idiographic approach to estimating models of dyadic interactions with differential equations.

We present an idiographic approach to modeling dyadic interactions using differential equations. Using data representing daily affect ratings from romantic relationships, we examined several models conceptualizing different types of dyadic interactions. We fitted each model to each of the dyads and the resulting AICc values were used to classify the most likely configuration of interaction for each dyad.

Estimation of subject-specific heritabilities from intra-individual variation: iFACE.

A new genetic factor model for multivariate phenotypic time series, iFACE, is presented which allows for the estimation of subject-specific model parameters of genetic and environmental factors. The iFACE was applied to multivariate EEG registrations obtained with single dizygotic twin pairs. The results showed evidence for considerable subject-specificity in heritabilities and environmental effects.

Emotional experience improves with age: evidence based on over 10 years of experience sampling.

Recent evidence suggests that emotional well-being improves from early adulthood to old age. This study used experience-sampling to examine the developmental course of emotional experience in a representative sample of adults spanning early to very late adulthood. Participants (N = 184, Wave 1; N = 191, Wave 2; N = 178, Wave 3) reported their emotional states at five randomly selected times each day for a one week period.

Dealing with short-term fluctuation in longitudinal research.

Objectives: Many analytical methods are not very sensitive to change because of the difficulty of distinguishing short-term fluctuation from the developmental change of primary interest. The current project investigated one possible solution to this problem in the form of a measurement-burst design in which research participants perform several versions of each test at each measurement occasion.

Methods: Over 1,200 adults across a wide-age range performed different versions of cognitive tests on several sessions at each measurement occasion.

Analyzing intra-person variation: hybridizing the ACE model with P-technique factor analysis and the idiographic filter.

Integrating idiographic and nomothetic approaches to the study of behavior has met with success via the idiographic filter (IF) which separates irrelevant inter-individual differences from relevant inter-individual similarities at the level of construct measurement in order to facilitate drawing conclusions regarding nomothetic relationships among the constructs. We propose an integration of the IF and the ACE behavior genetics models through the use of P-technique factor analysis and its dynamic factor analysis extensions and examine how it can strengthen the modeling of genetic and environmental effects in behavioral data representing intra-person variation, change, and process.

Issues in intraindividual variability: individual differences in equilibria and dynamics over multiple time scales.

This article addresses three issues germane to experimental design and statistical analysis of intraindividual variability such as the articles contained within this special section. First, the time scale of the measurement of a process can have profound effects on the outcome of analyses of the resulting time series. Measurement in time poses special problems in the design of experiments: the time scale of the measurements must be appropriate for the time scale of the process.

The Recoverability of P-technique Factor Analysis.

It seems that just when we are about to lay P-technique factor analysis finally to rest as obsolete because of newer, more sophisticated multivariate time-series models using latent variables-dynamic factor models-it rears its head to inform us that an obituary may be premature. We present the results of some simulations demonstrating that even though it does not explicitly model lagged information, P-technique's ability to recover the parameters of underlying dynamic processes involving lagged relations among the manifest variables is apparently robust and accurate. An empirical example is presented using 103 days of affective mood self-ratings from a young pregnant woman.

Age differences in dynamical emotion-cognition linkages.

The ability to maintain the separation between positive emotion and negative emotion in times of stress has been construed as a resilience mechanism. Emotional resiliency is particularly relevant in old age given concomitant declines in cognitive performance. In the present study, the authors examined the dynamical linkages among positive emotion, negative emotion, and cognition as individuals performed a complex cognitive task.

An Unscented Kalman Filter Approach to the Estimation of Nonlinear Dynamical Systems Models.

In the past several decades, methodologies used to estimate nonlinear relationships among latent variables have been developed almost exclusively to fit cross-sectional models. We present a relatively new estimation approach, the unscented Kalman filter (UKF), and illustrate its potential as a tool for fitting nonlinear dynamic models in two ways: (1) as a building block for approximating the log-likelihood of nonlinear state-space models and (2) to fit time-varying dynamic models wherein parameters are represented and estimated online as other latent variables. Furthermore, the substantive utility of the UKF is demonstrated using simulated examples of (1) the classical predator-prey model with time series and multiple-subject data, (2) the chaotic Lorenz system and (3) an empirical example of dyadic interaction.

Development and structural dynamics of personal life investment in old age.

The development of personal life investment (PLI) during old age was investigated with longitudinal and cross-sectional data from the Berlin Aging Study (N = 516, ages = 70-103 years). PLI measures motivational energy expended in life domains that require (obligatory PLI) or do not require (optional PLI) investment in old age. The authors used structural modeling to determine developmental trajectories and dynamics of the PLI types.

Short-term variability in cognitive performance and the calibration of longitudinal change.

Recent studies have documented that normal adults exhibit considerable variability in cognitive performance from one occasion to another. We investigated this phenomenon in a study in which 143 adults ranging from 18 to 97 years of age performed different versions of 13 cognitive tests in three separate sessions. Substantial within-person variability was apparent across 13 different cognitive variables, and there were also large individual differences in the magnitude of within-person variability.

Cognitive performance inconsistency: intraindividual change and variability.

Although many studies have examined inconsistency of cognitive performance, few have examined how inconsistency changes over time. 91 older adults (age 52 to 79) were tested weekly for 36 consecutive weeks on a series of multitrial memory speed (i.e.

General slowing or decreased inhibition? Mathematical models of age differences in cognitive functioning.

Researchers have attempted to explain age-related decrements in cognitive performance in terms of reduced processing speed or decreased ability to inhibit irrelevant thoughts. We present these ideas in the context of a dynamic model derived from extensions of the classical predator-prey equation. Reduced processing speed among older adults is represented by use of delays in the dynamic model, whereas the interference imposed by distractors is captured by use of the predator-prey interaction term.

Methodological and theoretical implications of intraindividual variability in perceptual-motor performance.

As an individual differences variable, lability (within-person variability) has often been neglected even though it has been shown to predict key outcomes such as mortality. We examine intraindividual variability in perceptual-motor performance and relate it to chronological age in a sample of adults. The magnitude of between-session variability was found to average between 25% and 50% of the between-person variability and was equivalent in magnitude to the variation that was apparent across an age range of 12 to 27 years in cross-sectional comparisons.

Assessing psychological change in adulthood: an overview of methodological issues.

This article reviews the current status of methods available for the analysis of psychological change in adulthood and aging. Enormous progress has been made in designing statistical models that can capture key aspects of intraindividual change, as reflected in techniques such as latent growth curve models and multilevel (random-effects) models. However, the rapid evolution of statistical innovations may have obscured the critical importance of addressing rival explanations for statistical outcomes, such as cohort differences or practice effects that could influence estimates of age-related change.

Modeling affective processes in dyadic relations via dynamic factor analysis.

An intraindividual variability design, including application of dynamic factor models, was used to examine the affective processes of a husband-wife dyad over 182 consecutive days. Structural equation analyses indicated differences in the affective structure between the husband and the wife, and these differences were characterized in terms of their factorial configuration and temporal organization. Examination of the dyad's affective dynamics revealed unidirectional (i.

Intraindividual variability and short-term change. Commentary.

Background: Interest in the study of intraindividual variability is growing rapidly.

Objective: The present collection of papers deals with both longer-term, growth and change and shorter-term intraindividual variability.

Methods: The papers emphasize primarily the former within the context of analyzing large, longitudinal data sets.

Elaborating the Differential in Differential Psychology.

The methods of differential psychology have contributed importantly to the current state of behavioral science, but their limitations continue to be well - publicized in the "experimental versus correlational" literature. The argument developed here is that the value of these methods has been constrained as much by the phenomena to which they are applied as by underlying flaws that render them inferior to classical experimental methods. Some applications of differential methods to alternative phenomena are examined that promise to broaden significantly the contribution that differential methods can make to our understanding of behavior and behavior change.