Lack of group-to-individual generalizability is a threat to human subjects research

Abstract

Only for ergodic processes will inferences based on group-level data generalize to individual experience or behavior. Because human social and psychological processes typically have an individually variable and time-varying nature, they are unlikely to be ergodic. In this paper, six studies with a repeated-measure design were used for symmetric comparisons of interindividual and intraindividual variation. Our results delineate the potential scope and impact of nonergodic data in human subjects research. Analyses across six samples (with 87-94 participants and an equal number of assessments per participant) showed some degree of agreement in central tendency estimates (mean) between groups and individuals across constructs and data collection paradigms. However, the variance around the expected value was two to four times larger within individuals than within groups. This suggests that literatures in social and medical sciences may overestimate the accuracy of aggregated statistical estimates. This observation could have serious consequences for how we understand the consistency between group and individual correlations, and the generalizability of conclusions between domains. Researchers should explicitly test for equivalence of processes at the individual and group level across the social and medical sciences.

Keywords: ecological fallacy; generalizability; idiographic science; replicability; research methodology.

Fig. 1.

Histograms for intraindividual (red) and interindividual (blue) correlations for four bivariate relationships in sample 1. Top depicts intraindividual correlations calculated from raw data. Bottom depicts intraindividual correlations calculated from data with temporal dependence removed.

Fig. 2.

Histograms for intraindividual (red) and interindividual (blue) correlations for RSA and HR. Left depicts intraindividual correlations calculated from raw data. Right depicts intraindividual correlations calculated from data with temporal dependence removed.

Fig. 3.

Histograms for intraindividual (red) and interindividual (blue) correlations between positive affect (PA) and negative affect (NA) in samples 3, 4, and 5. Top depicts intraindividual correlations calculated from raw data. Bottom depicts intraindividual correlations calculated from data with temporal dependence removed.

Fig. 4.

Density plots for the distributions of correlations in sample 6 between low-arousal positive affect (PA) and negative affect (NA) (Left) and high-arousal PA and NA (Right). Red indicates distributions related to the 535 individual respondents. Blue indicates the distributions of the 85 cross-sectional comparison datasets. Intraindividual correlations were calculated from raw data (Top), and data with temporal dependence removed (Bottom).