The study utilized the covariance structure comparison methodology - Multigroup Analysis in Structural Equation Modeling - evaluating measurement equivalence of English and Spanish versions of an employee opinion survey. The concept of measurement equivalence was defined as consisting of four components: sample equivalence, semantic equivalence, conceptual equivalence and scalar equivalence. The results revealed that the two language versions of the survey exhibited acceptable measurement equivalence across five survey dimensions Communications, Supervision, Leadership, Job Content & Satisfaction and Company Image & Commitment. Contrary to the study second hypothesis, there was no meaningful difference in opinion scores between English-speaking and Spanish-speaking respondents on the latent construct of Job Content & Satisfaction.

This dissertation study was designed to examine measurement equivalence of the Center for Epidemiological Studies Depression (CES-D) Scale across White, African American, and Mexican American elders. Specific aims were to identify race/ethnicity-, sociodemographic-, and acculturation and instrument language-related measurement bias in the CES-D. Three studies were conducted in this dissertation to accomplish these aims. Two existing national datasets were used: the New Haven Established Populations for Epidemiologic Studies of the Elderly (EPESE) for the White and African American samples and the Hispanic Established Populations for Epidemiologic Studies of the Elderly (H-EPESE) for the Mexican-American sample. Differential item functioning (DIF) analyses were conducted using both confirmatory factor analysis (CFA) and item response theory (IRT) methods. Study 1 focused on the role of race/ethnicity on the measurement bias in the CES-D. Results from Study 1 showed a lack of measurement equivalence of the CES-D among Mexican Americans in the comparison with both Whites and Blacks. Race/ethnicity-specific items were also identified in Study 1: two interpersonal relation items in Blacks and four positive affect items in Mexican Americans. Study 2 focused on identifying sociodemographic-related measurement bias in responses to the CES-D among diverse racial/ethnic groups. Results from Study 2 showed that gender and educational attainment affected item bias in the CES-D. The interaction between gender and educational level and race/ethnicity was also found in Study 2: Mexican American women and lower educated Blacks had a greater predisposition to endorse the 'crying' item. Focusing on Mexican American elders, Study 3 examined how level of acculturation and language influence responses to the CES-D. In Study 3, acculturation and instrument language-biased items were identified in Mexican American elders. Study 3 also suggested that acculturation-bias was entirely explained by whether the CES-D was administered in the English or the Spanish versions. Possible reasons for item bias on the CES-D are discussed in the context of sociocultural differences in each substudy. Findings from this dissertation provide a broader understanding of sociocultural group differences in depressive symptom measures among racially/ethnically diverse older adults and yield research and practice implications for the use of standard screening tools for depression.

While assessing emotions, behaviors or performance of preschoolers and young children, scores from adults such as parent psychiatrist and teacher ratings are used rather scores from children themselves. Data from parent ratings or from parents and teachers are often nested such as students are within teachers and a child is within their parents. This popular nested feature of data in educational, social and behavioral sciences makes measurement invariance (MI) testing across informants of children methodologically challenging. There was lack of studies that take into account the nested structure of data in MI testing for multiple adult informants, especially no simulation study that examines the performance of different models used to test MI across different raters. This dissertation focused on two specific nesting data types in testing MI between adult raters of children: paired and partial nesting. For the paired data, the independence assumption of regular MI testing is often violated because the two informants (e.g., father and mother) rate the same child and their scores are anticipated to be related or dependent. The partial nesting data refers to the research situation where teacher and parent ratings are compared. In this scenario, it is common that each parent has only one child to rate while each teacher has multiple children in their classroom. Thus, in case of teacher and parent ratings of the same children, data are repeated measures and also partially nested. Because of these unique features of data, MI testing between adult informants of children requires statistical models that take into account different types of data dependency. I proposed and evaluated the performance of the two statistical models that can handle repeated measures and partial nesting with several simulated research scenarios in addition to one commonly used and one potentially appropriate statistical models across several research scenario. Results of the two simulation studies in this dissertation showed that for the paired data, both multiple-group confirmatory factor analysis (CFA) and repeated measure CFA models were able to detect scalar invariance most of the time using Δχ2 test and ΔCFI. Although the multiple-group CFA (Model 2) was able to detect scalar invariance better than the repeated measure CFA model (Model 1), the detection rates of Model 1 were still at the high level (88% - 91% using Δχ2 test and 84% - 100% using ΔCFI or ΔRMSEA). For configural invariance and metric invariance conditions for the paired data, Model 1 had higher detection rate than Model 2 in almost examined research scenario in this dissertation. Particularly while Model 1 could detect noninvariance (either in intercepts only or in both intercepts and factor loadings) than Model 2 for paired data most of the time, Model 2 could rarely catch it if using suggested cut-off of 0.01 for RMSEA differences. For the paired data, although both Models 1 and 2 could be a good choice to test measurement invariance, Model 1 might be favored if researchers are more interested in detecting noninvariance due to its overall high detection rates for all three levels (i.e. configural, metric, and scalar) of measurement invariance. For scalar invariance with partially nested data, both multilevel repeated measure CFA and design-based multilevel CFA could detect invariance most of the time (from 81% to 100% of examined cases) with slightly higher detection rate for the former model than the later. Multiple-group CFA model hardly detect scalar invariance except when ICC was small. The detection rates for configural invariance using Δχ2 test or Satorra-Bentler LRT were also highest for Model 3 (82% to 100% except only two conditions with detection rates of 61%), following by Model 5 and lowest Model 4. Models 4 and 5 could reach these rates only with the largest sample sizes (i.e., large number of cluster or large cluster size or large in both factors) when the magnitude of noninvariance was small. Unlike scalar and configural invariance, the ability to detect metric invariance was highest for Model 4, following by Model 5 and lowest for Model 3 across many conditions using all of the three performance criteria. As higher detection rates for all configural and scalar invariance, and moderate detection rates for many metric invariance conditions (except cases of small number of clusters combined with large ICC), Model 3 could be a good candidate to test measurement invariance with partially nested data when having sufficient number of clusters or if having small number of clusters with small ICC. Model 5 might be also a reasonable option for this type of data if both the number of clusters and cluster size were large (i.e., 80 and 20, respectively), or either one of these two factors was large coupled with small ICC. If ICC is not small, it is recommended to have a large number of clusters or combination of large number of clusters and large cluster size to ensure high detection rates of measurement invariance for partially nested data. As multiple group CFA had better and reasonable detection rates than the design-based and multilevel repeated measure CFA models cross configural, metric and scalar invariance with the conditions of small cluster size (10) and small ICC (0.13), researchers can consider using this model to test measurement invariance when they can only collect 10 participants within a cluster (e.g. students within a classroom) and there is small degree of data dependency (e.g. small variance between clusters) in the data.

In this study, the relationship of autobiographical memory, implicit motivation, sociocultural orientation, and childhood variables was investigated cross-culturally. A German sample reflecting a prototypical independent context (n=100), and a Chinese (n = 77) and Cameroonian sample (n = 68) from a prototypical interdependent context were selected. Participants were asked to report their earliest childhood memories, to answer socio-demographic questions, to complete the Operant Multimotive Test as a measure of their implicit motivation, and two self-report scales to indicate their sociocultural orientation. Special attention was given to considerations of methodological equivalence across cultures.It was expected that (1) Chinese and Cameroonian participants recall more oriented towards others than German participants, and that (2) individuals from a social-oriented childhood context make more use of the social function of autobiographical recall, and finally that (3) implicit motivation and sociocultural orientation predict autobiographical memory across cultures.Results indicate that Cameroonian and Chinese participants generally make more use of the social function of autobiographical memory than do German participants. Furthermore, the more siblings an individual has, the more she/he makes use of the social function. Missing effects of implicit motivation and sociocultural orientation on interindividual differences in autobiographical memory are accounted for by methodological constraints.

No description available.

Measurement problems in terms of different understanding of the meaning, concepts and implications of survey questions as well as tendencies to different response-sets (e.g. acquiescence or social desirability) are reoccurring problems in comparative migration research. Cultural factors, time-varying effects and survey design lead to response biases. It could be shown that depending on the region of origin, migrants tend to extreme or centred responding behaviour. Macroscale changes in attitudes towards disclosure of personal information influence acquiescent biases. Therefore, the question arises whether the presence of measurement equivalence can be assumed, especially within instruments regarding subjective feelings, when comparing migrant and native populations. The aim of the study is to test for intercultural and longitudinal equivalence of the Health Short Form 12 - items scale (SF -12), trying to answer the question whether this instrument is useful to compare health of migrants and native Germans over time. The study contributes to the ongoing discussion on measurement equivalence of the SF -12 by including variables concerning integration and assimilation, employment, family status and varying types of migration and years since migration to the analysis. Using a Multiple Group Structural Equation Modelling approach analyzing longitudinal data of the German Socioeconomic Panel (SOEP), we test the validity and measurement equivalence (configural, metric and scalar invariance) of the latent construct ‘health’ over time and between (non-)migration groups. In addition, different item functioning can be detected for a series of covariates. The study concludes in recommending a reduced version of the SF-12 to improve the avoidance of measurement artefacts when comparing the health of migrants and native Germans.

Golembiewski, Billingsly, and Yeager (1976) conceptualized three distinct types of change that might result from development interventions, called alpha, beta, and gamma change. Recent research has found that beta and gamma change do occur as hypothesized, but the phenomena are somewhat infrequent and the precise conditions under which they occur have not been established. This study used confirmatory factor analysis and item response theory to identify gamma and beta change on a multidimensional, multisource managerial performance appraisal instrument and to examine relations among the change types, training program content, and raters' implicit theories of performance. Results suggested that coverage in training was a necessary but not sufficient condition for beta and gamma change to occur. Further, although gamma change was detected only in the trainee group, beta change was detected in self-ratings from trainees and in ratings collected from their superiors. Because trainees' superiors were involved in post-training follow-up, this finding was interpreted as a possible diffusion of treatments effect (Campbell & Stanley, 1963). Contrary to expectations, there were no interpretable relations between raters' implicit theories of performance and either of the change types. Perhaps relatedly, more implicit theory change was detected among individuals providing observer ratings than in the trainees themselves. The implications of these findings for future research on plural change were discussed. / Ph. D.

The measurement of reliable and valid indicators of early child development is necessary for assessing phenomena and is useful in the monitoring of ongoing efforts to eradicate inequalities in the social determinants of health. There is an increasing awareness of the contextual, cultural, and developmental influences on constructs used in early child development (ECD) research. Using a measurement perspective, this dissertation examined the issue of measurement invariance and psychometric validity in early child development research. A construct violates the principle of invariance when two persons from different populations who are theoretically identical on the construct being measured have different scores on it. This dissertation consists of three journal-style manuscripts (published or under review) that were used as examples to address the importance of the issue of measurement invariance and psychometric validity in ECD research using data from two unique areas: autism and executive functioning. The three data sets were collected on pre-school children with parents and or teachers as informants and were chosen to represent different levels of data collection – clinical, community, and population. These data sets allowed for the examination of measurement invariance by type of informant, sex, and age of child. The results from the three studies illustrate the importance of assessing measurement invariance in ECD and whether or not the instruments examined can be used to assess sub-group differences with confidence. A lack of measurement invariance found for two of the studies, suggests that observed group differences in latent constructs could be attributed, in part, to measurement bias. More importantly, bias in the measurement of the constructs of severity of social impairment symptoms in autism, and executive functioning across groups could have an impact on services such as patient treatment. These biases could also influence public policy development, particularly when there may be an underlying need for a cross-group approach where belief systems may affect the meaning and structure of constructs. In summary, measurement invariance should be a prerequisite for making any meaningful comparisons across groups. A requirement of establishing measurement invariance should be included in the guidelines for comparative research studies as a necessary first step before an instrument is adopted for use.

The measurement of reliable and valid indicators of early child development is necessary for assessing phenomena and is useful in the monitoring of ongoing efforts to eradicate inequalities in the social determinants of health. There is an increasing awareness of the contextual, cultural, and developmental influences on constructs used in early child development (ECD) research. Using a measurement perspective, this dissertation examined the issue of measurement invariance and psychometric validity in early child development research. A construct violates the principle of invariance when two persons from different populations who are theoretically identical on the construct being measured have different scores on it. This dissertation consists of three journal-style manuscripts (published or under review) that were used as examples to address the importance of the issue of measurement invariance and psychometric validity in ECD research using data from two unique areas: autism and executive functioning. The three data sets were collected on pre-school children with parents and or teachers as informants and were chosen to represent different levels of data collection – clinical, community, and population. These data sets allowed for the examination of measurement invariance by type of informant, sex, and age of child. The results from the three studies illustrate the importance of assessing measurement invariance in ECD and whether or not the instruments examined can be used to assess sub-group differences with confidence. A lack of measurement invariance found for two of the studies, suggests that observed group differences in latent constructs could be attributed, in part, to measurement bias. More importantly, bias in the measurement of the constructs of severity of social impairment symptoms in autism, and executive functioning across groups could have an impact on services such as patient treatment. These biases could also influence public policy development, particularly when there may be an underlying need for a cross-group approach where belief systems may affect the meaning and structure of constructs. In summary, measurement invariance should be a prerequisite for making any meaningful comparisons across groups. A requirement of establishing measurement invariance should be included in the guidelines for comparative research studies as a necessary first step before an instrument is adopted for use.

No description available.