“Psychological Testing and Psychological Assessment: A Review of Evidence and Issues”, Gregory J. Meyer, Stephen E. Finn, Lorraine D. Eyde, Gary G. Kay, Kevin L. Moreland, Robert R. Dies, Elena J. Eisman, Tom W. Kubiszyn, Geoffrey M. Reed2001-02 (psychiatry, psychology, meta-analysis)⁠:

This article summarizes evidence and issues associated with psychological assessment.

Data from >125 meta-analyses on test validity and 800 samples examining multimethod assessment suggest 4 general conclusions: (1) Psychological test validity is strong and compelling, (2) psychological test validity is comparable to medical test validity, (3) distinct assessment methods provide unique sources of information, and (4) clinicians who rely exclusively on interviews are prone to incomplete understandings.

Following principles for optimal nomothetic research, the authors suggest that a multimethod assessment battery provides a structured means for skilled clinicians to maximize the validity of individualized assessments. Future investigations should move beyond an examination of test scales to focus more on the role of psychologists who use tests as helpful tools to furnish patients and referral sources with professional consultation.

…To ensure a general understanding of what constitutes a small or large correlation (our effect size measure), we review a variety of nontest correlations culled from psychology, medicine, and everyday life…A Foundation for Understanding Testing and Assessment Validity Evidence: To summarize the validity literature on psychological testing and assessment, we use the correlation coefficient as our effect size index. In this context, the effect size quantifies the strength of association between a predictor test scale and a relevant criterion variable. To judge whether the test validity findings are poor, moderate, or substantial, it helps to be clear on the circumstances when one is likely to see a correlation of 0.10, 0.20, 0.30, and so on. Therefore, before delving into the literature on testing and assessment, we present an overview of some non-test-related correlational values. 3 We believe this is important for several reasons. Because psychology has historically emphasized statistical-significance over effect size magnitudes and because it is very hard to recognize effect magnitudes from many univariate statistics (eg. t, F, χ²) or multivariate analyses, it is often difficult to appreciate the size of the associations that are studied in psychology or encountered in daily life.