A structural model for postpartum responses to the somatic and cognitive items on the Beck Depression Inventory

A distinction can be drawn between those items on the Beck Depression Inventory (BDI) that reflect mainly cognitive and emotional symptoms and those that reflect somatic symptoms. Responses to the BDI were obtained from women at 3, 6, 9, and 24 weeks postpartum. The covariances of cognitive and somatic symptom scores across the four time points were closely fit by a structural equations model referred to as the simplex. The modeling indicates that earlier cognitive scores directly predict later somatic scores but that early somatic scores do not directly predict later cognitive scores. Other data confirm the results.Much of this research was supported while the first author was an NIMH Fellow at the University of Iowa (MH15168).     

Multifactor measurement of bodily feelings: Conceptual development,scale construction,and empirical validation

A series of studies is described demonstrating a coherent exploratory and confirmatory factor-analytic approach to the scaling of self-reported bodily feelings. This approach attempts to optimize the orthogonality, parsimony, and meaningfulness of a multifactor inventory. Psychometric properties of the resulting 35-item Bodily Feeling Scale (BFS) are presented and its comparability with other inventories is discussed. A validity study using item-content-based scales of the Minnesota Multiphasic Personality Inventory showed both concurrent and discriminative validity of the BFS. Implications for clinical and research utility are discussed.Portions of this research were conducted while the first author was supported by a University Graduate Fellowship awarded by the Graduate School of Arts and Sciences at Vanderbilt University.Professor Nunnally passed away in August 1982. His major contributions to the several stages of this research program are recognized through coauthorship.     

On structural equation modeling with data that are not missing completely at random

A general latent variable model is given which includes the specification of a missing data mechanism. This framework allows for an elucidating discussion of existing general multivariate theory bearing on maximum likelihood estimation with missing data. Here, missing completely at random is not a prerequisite for unbiased estimation in large samples, as when using the traditional listwise or pairwise present data approaches. The theory is connected with old and new results in the area of selection and factorial invariance. It is pointed out that in many applications, maximum likelihood estimation with missing data may be carried out by existing structural equation modeling software, such as LISREL and LISCOMP. Several sets of artifical data are generated within the general model framework. The proposed estimator is compared to the two traditional ones and found superior.The research of the first author was supported by grant No. SES-8312583 from the National Science Foundation and by a Spencer Foundation grant. We wish to thank Chuen-Rong Chan for drawing the path diagram.     

A taxonomy of item response models

A number of models for categorical item response data have been proposed in recent years. The models appear to be quite different. However, they may usefully be organized as members of only three distinct classes, within which the models are distinguished only by assumptions and constraints on their parameters. “Difference models” are appropriate for ordered responses, “divide-by-total” models may be used for either ordered or nominal responses, and “left-side added” models are used for multiple-choice responses with guessing. The details of the taxonomy and the models are described in this paper. The present study was supported in part by two postdoctoral fellowships awarded to Lynne Steinberg: an Educational Testing Service Postdoctoral Fellowship at ETS, Princeton, NJ and an NIMH Individual National Research Service Award at Stanford University, Stanford, CA. Helpful comments by the editor and three anonymous reviewers are gratefully acknowledged.     

Longitudinal relations among perceived parental warmth,self-esteem and social behaviours from middle childhood to early adolescence in China: Disentangling between- and within-person associations

Although several studies have addressed the relations between perceived parental warmth and social behaviours, few have distinguished their between- and within-person effects or explored their within-person mediating mechanisms. This study examined the transactional relations among perceived parental warmth (i.e. maternal warmth and paternal warmth), children's self-esteem and children's positive/negative social behaviours (i.e. prosocial behaviour and delinquent behaviour) along with the mediating role of self-esteem after disentangling between- and within-person effects. A total of 4315 Chinese elementary children (44.9% girls; M_age = 9.93 years, SD = 0.73) completed relevant measures on four occasions employing 6-month intervals. Results of random-intercept cross-lagged panel models showed that (a) perceived parental warmth reciprocally and positively predicted prosocial behaviour and self-esteem; (b) perceived paternal warmth reciprocally and negatively predicted delinquent behaviour; (c) self-esteem reciprocally predicted prosocial and delinquent behaviour; (d) perceived maternal warmth reciprocally and positively predicted prosocial behaviour through self-esteem; (e) perceived parental warmth reciprocally and negatively predicted delinquent behaviour through self-esteem; and (f) perceived maternal and paternal warmth differed in their relations with prosocial and delinquent behaviours through self-esteem. These findings illuminated the complicated longitudinal within-person interactions among perceived parental warmth, self-esteem, and social behaviours, the specific mediating mechanism of self-esteem, and the differing results associated with perceived maternal and paternal warmth, all of which yield significant implications for assessments and early interventions aimed to promote positive social behaviour.     

Premature conclusions about the signal-to-noise ratio in structural equation modeling research: A commentary on Yuan and Fang (2023)

In a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller standard errors, and thus corresponds to greater values of the [SNR].” In our commentary, we show that Yuan and Fang have made several incorrect assumptions and claims. Consequently, we recommend that empirical researchers not base their methodological choice regarding CB-SEM and regression analysis with composites on the findings of Yuan and Fang as these findings are premature and require further research.     

The factor structure of the Multiple Affect Adjective Check List-Revised (MAACL-R): Some statistical considerations

In response to Zuckerman's comments on my factor analyses of the MAACL-R, I focus on the statistical issues of the cutoff criterion for factor loadings and the evidence for the discriminant validity of the five-factor solution. Based upon the conclusions I draw in these two areas, I recommend that researchers either (a) use the two factor solution to the MAACL-R represented in the summary scores of Dysphoria and Positive Affect + Sensation Seeking or (b) include all MAACL-R scales in their studies and analyze their data to determine whether it is statistically appropriate to report results from a single scale (A, D, H, PA, or SS) rather than from the summary scores.     

Factor structure of the mobility inventory for agoraphobia: A validational study with australian samples of agoraphobic patients

This study examines the factor structure of the Mobility Inventory for Agoraphobia and attempts to validate the inventory, using an Australian sample of agoraphobic patients, by comparison with other scales. One hundred twentyfour panic disorder with agoraphobia patients were studied. Factor analysis showed that a two-factor solution was the most suitable both when subjects were accompanied (accompanied condition) and when alone (alone condition). Factor I represented public, crowded, or social situations including department stores, supermarkets, restaurants, theaters, and panics and social gatherings. Factor II reflected enclosed or riding situations such as elevators, parking garages, enclosed spaces, and riding in subways or airplanes. These two factors accounted for 46.6% and 44.3% of the variance on the accompanied condition and the alone condition, respectively. The Mobility Inventory was significantly correlated with the Agoraphobia factor of the Fear Questionnaire and the Social Avoidance and Distress scale. These results indicated that the Mobility Inventory is a valid instrument to measure agoraphobic behavior.     

Psychometric properties and factor structure of the Fear Questionnaire phobia subscale items in two normative samples

Normative data for the Fear Questionnaire (Marks & Mathews, 1979), a popular self-report instrument measuring phobic concerns, were collected from both a community and a collegiate sample. The covariation and internal consistency of the blood-injury phobia (BI), social phobia (SO), and agoraphobia (AG) subscales were assessed in each sample, and the factor structure of the items from these three subscales was examined. Results indicated that, in general, community subjects reported more phobic concerns than did collegiate subjects, and females reported greater phobic concerns than did males. Results from confirmatory factor analyses suggest that the three factors of BI, SO, and AG did not emerge from either data set. Follow-up exploratory factor analyses did identify the general factors of blood-injury phobia and agoraphobia. Normative data from the present study are compared to those obtained previously, and directions for future research are provided.