Survey data in social, behavioral, and health sciences often contain many variables (p). Structural equation modeling (SEM) is commonly used to analyze such data. With a sufficient number of participants (N), SEM enables researchers to easily set up and reliably test hypothetical relationships among theoretical constructs as well as those between the constructs and their observed indicators. However, SEM analyses with small N or large p have been shown to be problematic. This article reviews issues and solutions for SEM with small N, especially when p is large. The topics addressed include methods for parameter estimation, test statistics for overall model evaluation, and reliable standard errors for evaluating the significance of parameter estimates. Previous recommendations on required sample size N are also examined together with more recent developments. In particular, the requirement for N with conventional methods can be a lot more than expected, whereas new advances and developments can reduce the requirement for N substantially. The issues and developments for SEM with many variables described in this article not only let applied researchers be aware of the cutting edge methodology for SEM with big data as characterized by a large p but also highlight the challenges that methodologists need to face in further investigation.

Background Optimal Matching Theory (OMT; [1]) posits that the effects of social support are enhanced when its provision is matched with need for support. We hypothesized that matching received social support with the needs of persons with cancer and cancer survivors would be related to better psychosocial adjustment than a mismatched condition. Method In a cross-sectional design, Sample 1, 171 cancer patients, and Sample 2, 118 cancer survivors, completed measures of emotional and instrumental received support, physical debilitation, and psychological distress. Results The OMT model was confirmed; those needing support (i.e., greater physical debilitation), who did not receive it, experienced more distress than those who needed support and received it. Patients in treatment benefited from the matching of need and provision for both emotional and instrumental support; whereas, survivors only benefited from the matching of emotional support. Conclusions The results suggest that social support is contextualized by the degree of physical impairment and may be somewhat different for cancer patients in treatment compared to cancer survivors. The transition to cancer survivorship may involve a transformation in the need for as well as the type and amount of received social support.

Objective Social relationship coping efficacy (SRCE) is the confidence to engage in behaviors that can maintain or enhance close social relationships in the context of illness. This study focused on psychometric analyses of the SRCE scale and its role in maintaining or enhancing personal relationships, social support, and quality of life (QOL). Method A mixed diagnosis sample (N = 151) of cancer patients completed a variety of measures: physical debilitation, received emotional and instrumental support, SRCE, and QOL. Results The SRCE scale is a 10‐item, one‐factor, internally reliable (α = 0.965) measure with strong concurrent validity in relation to measures of social support. SRCE fully mediated the relationship between physical debilitation and both instrumental and emotional received support. SRCE also was directly related to both social/family well‐being and psychological distress, and this relationship was also partially mediated by social support. Conclusions The results corroborated that SRCE might account for changes in both instrumental and emotional support. Also, the direct and indirect relationship (mediated by social support) of SRCE with both social/family well‐being and distress indicated that interventions to increase SRCE with those at risk for social support loss may bolster social support in personal relationships as well as enhance emotional well‐being and quality of life.

Based on self-regulation and self-efficacy theories, the Cancer Behavior Inventory (CBI; Heitzmann et al., 2011; Merluzzi & Martinez Sanchez, 1997; Merluzzi, Nairn, Hegde, Martinez Sanchez, & Dunn, 2001) was developed as a measure of self-efficacy strategies for coping with cancer. In the latest revision, CBI-V3.0, a number of psychometric and empirical advances were made: (a) the reading level was reduced to 6th-grade level; (b) individual interviews and focus groups were used to revise items; (c) a new spiritual coping subscale was added; (d) data were collected from 4 samples (total N = 1,405) to conduct an exploratory factor analysis with targeted rotation, 2 confirmatory factor analyses, and differential item functioning; (e) item trimming was used to reduce the total number to 27; (f) internal consistency and test-retest reliability were computed; and (g) extensive validity testing was conducted. The results, which build upon the strengths of prior versions, confirm a structurally and psychometrically sound and unbiased measure of self-efficacy strategies for coping with cancer with a reduced number of items for ease of administration. The factors include Maintaining Activity and Independence, Seeking and Understanding Medical Information, Emotion Regulation, Coping With Treatment Related Side Effects, Accepting Cancer/Maintaining a Positive Attitude, Seeking Social Support, and Using Spiritual Coping. Internal consistency (α = .946), test-retest reliability (r = .890; 4 months), and validity coefficients with a variety of relevant measures indicated strong psychometric properties. The new 27-item CBI-V3.0 has both research utility and clinical utility as a screening and treatment-planning measure of self-efficacy strategies for coping with cancer. (PsycINFO Database Record

The structure and measurement of occupational fraud rationalization as one of the motivations for fraudulent behavior has been a major obstacle in theoretical research and practical problems. In order to answer the fundamental question, “What does cognitive rationalization of occupational fraud involve?,” this paper explored the structure and scale development of the internal psychological factors of occupational fraud rationalization. Several research methods were used for this purpose, such as data collection, research interviews, review & verification, project purification, structural verification, and reliability & validity test. The results showed that, based on the internal structure, occupational fraud rationalization presented second-order three-dimensional and first-order eight-dimensional factors. Further, a formal scale containing 27 items related to the structure of the metric was constructed to measure the occupational fraud rationalization. In terms of variable correlations, this paper empirically tested the criterion validity of occupational fraud rationalization from the perspective of personality traits. The result revealed a significant positive (negative) correlation between Machiavellian traits (empathy traits) and occupational fraud rationalization, respectively. In conclusion, this paper provides an attempt to address the cognitive and measurement challenges of occupational fraud rationalization, expanding the application and development of moral disengagement theory in the field of occupational fraud and laying some groundwork for subsequent research and development.