Cross-classified Multilevel Models Research Articles

Student characteristics and effort during test-taking

BackgroundAchievement tests are designed as measurement tools for student knowledge and learning, but also reflect student effort during the test. Understanding better what determines differences in (different dimensions of) effort can help in understanding what measured achievement differences reflect. AimWe analyze how test-taking effort relates to students’ demographic characteristics, past attainment and personality traits. Data13,791 9th grade students in the Netherlands, administered in 2012, 2014 and 2016, answering a total of 449,956 observations. MethodsWe distinguish between two measures of effort: solution behavior and response time given solution behavior. We estimate multi-level cross-classified models that include individual and test characteristics as predictors. We further include interaction terms between question position and individual characteristics, to identify how effort decline across the test differs by student type. ResultsGirls, high achievers, more agreeable, more conscientious and less extravert students exert more effort. Differences by past achievement are especially large and further increase along the test, while differences in other characteristics tend to be more stable. Effort differences by socioeconomic status are relatively small. ConclusionsSystematic differences between different types of students can partly reflect differences in test effort across these groups. Thus, test effort should be considered when analyzing achievement gaps and differences across learning outcomes. Tests with different test lengths imply different measures of educational inequality through differential effort declines.

Geographic Variation of Antidementia and Antipsychotic Medication Use Among US Nursing Home Residents With Dementia.

Several antidementia medications have been approved for symptomatic treatment of cognitive and functional impairment due to Alzheimer disease. Antipsychotics are often prescribed off-label for behavioral symptoms. The aim of this study was to describe the basis for regional variation in antidementia and antipsychotic medication use. US nursing homes (n=9735), hospital referral regions (HRR; n=289). Long-stay residents with dementia (n=273,004). Using 2018 Minimum Data Set 3.0 linked to Medicare data, facility information, and Dartmouth Atlas files, we calculated prevalence of use and separate multilevel logistic models [outcomes: memantine, cholinesterase inhibitor (ChEI), antipsychotic use] estimated adjusted odds ratios (aOR) and 95% CIs for resident, facility, and HRR characteristics. We then fit a series of cross-classified multilevel logistic models to estimate the proportional change in cluster variance (PCV). Overall, 20.9% used antipsychotics, 16.1% used memantine, and 23.3% used ChEIs. For antipsychotics, facility factors [eg, use of physical restraints (aOR: 1.08; 95% CI: 1.05-1.11) or poor staffing ratings (aOR: 1.10; 95% CI: 1.06-1.14)] were associated with more antipsychotic use. Nursing homes in HRRs with the highest health care utilization had greater antidementia drug use (aOR memantine: 1.68; 95% CI: 1.44-1.96). Resident/facility factors accounted for much regional variation in antipsychotics (PCV STATE : 27.80%; PCV HRR : 39.54%). For antidementia medications, HRR-level factors accounted for most regional variation (memantine PCV STATE : 37.44%; ChEI PCV STATE : 39.02%). Regional variations exist in antipsychotic and antidementia medication use among nursing home residents with dementia suggesting the need for evidence-based protocols to guide the use of these medications.

Predictors of Complicated Grief During the COVID-19 Pandemic: A Cross-Classified Analysis.

The COVID-19 pandemic left many people grieving multiple deaths and at risk for developing symptoms of complicated grief (CG). The present study is a prospective examination of the role of neuroticism and social support in the development of CG symptoms. Findings from cross-classified multilevel models pointed to neuroticism as a risk factor for subsequent CG symptoms. Social support had a stress-buffering effect, emerging as a protective factor following the loss of a first degree relative. More recent loss and younger age of the deceased were both independently associated with heightened CG symptoms. Results from the present study provide insight into heterogeneity in CG symptom development at the between-person level, and variability in CG symptoms within individuals in response to different deaths. Findings could therefore aid in the identification of those at risk for the development of CG symptoms.

Student situational engagement and its associations with regard for adolescent perspectives, productivity, and instructional learning formats in the classroom

Teacher–student interactions are considered to influence student engagement. As such, building on the teaching through interaction framework, this study presents an investigation of specific features of teacher–student interactions (regard for adolescent perspectives, productivity, and instructional learning formats) and their association with student engagement in a particular lesson. The sample consisted of 404 8th–10th grade students from 18 classrooms. The data comprised 87 videorecorded lessons, divided into 216 observation cycles, coded using the Classroom Assessment Scoring System – Secondary observational instrument. Additionally, the students’ self-reports of their situational engagement were collected using the web-based In Situations (InSitu) instrument at the end of six separate lessons. The data were analysed with cross-classified multilevel structural equation modelling, with engagement ratings cross-classified by students and lessons. In line with the study hypothesis, the results revealed positive associations between situational engagement and the two dimensions of regard for adolescent perspectives and instructional learning formats, yet there were unexpected negative associations with productivity.

Innovation knowledge exchange within Chaebols and the ownership structure of their foreign subsidiaries

PurposeThis study examines how the characteristics of innovation knowledge exchanged among affiliate firms affect the ownership strategies adopted for their foreign subsidiaries.Design/methodology/approachThis study employs a cross-classified multilevel model to examine a sample of 185 Korean manufacturing affiliates derived from 49 Chaebols engaged in international diversification, along with their 1,110 foreign manufacturing subsidiaries.FindingsWhile exploratory innovation knowledge exchange lowers the affiliate's level of ownership in its foreign subsidiary, exploitative innovation knowledge exchange rather increases the affiliate's level of ownership in its foreign subsidiary.Research limitations/implicationsThis study advances the literature on intrafirm knowledge exchange by highlighting it as a determinant of ownership strategies. The study further shows that the characteristics of knowledge exchanged at the affiliate level not only determine the ownership structure but also have the potential to shape the direction in which the subsidiary develops its competencies.Practical implicationsThis study has practical implications for the managers of business group affiliates. The results suggest that managers should adapt their ownership strategies according to the type of knowledge exchanged at the affiliate level to achieve a balanced and synergistic effect on intraorganizational knowledge exchange.Originality/valuePrevious studies have extensively explored the performance implications related to knowledge exchange. However, there is a notable gap in understanding the mechanisms through which the value of knowledge transferred within an affiliate is realized. To address this gap, this study focuses on ownership strategy as a crucial factor and empirically examines how the characteristics of innovation knowledge exchanged among affiliate firms influence the ownership strategies adopted for their foreign subsidiaries. By investigating this relationship, this study provides valuable insights into the complex dynamics of knowledge exchange and its effect on ownership decisions within business group affiliates.

Abstract 4846: Geographic and physician-level variation in the use of hypofractionated radiotherapy for breast cancer in the U.S.: A cross-classified multilevel analysis

Abstract Hypofractionated whole-breast irradiation (HF-WBI), a radiotherapy with a larger dose per fraction and a shorter schedule for early-stage breast cancer patients post breast-conserving surgery, shows equivalent safety and efficacy compared to conventionally fractionated whole-breast irradiation (CF-WBI) regarding local recurrence and disease-free survival. While several countries have set HF-WBI as the preferred standard of care for these patients, its uptake in the U.S. has lagged behind expectations. We used the Health Care Cost Institute (HCCI) database 2008-2017, covering a third of the U.S. employer-sponsored insurance population, to identify early-stage breast cancer patients. Patients were clustered at different geographic levels (Census region, state, core-based statistical area (CBSA), hospital referral region of Dartmouth Atlas, and zip code) and the radiation oncologist level. These two levels are cross-nested. We used a Bayesian cross-classified multilevel logistic model to simultaneously model the geographic units variability and physician-level variability in HF-WBI use across the U.S. Variation metrics included intracluster correlation coefficient (ICC) and median odds ratios (MOR). ICC with a value of 0 is equivalent to MOR of 1, indicating identical outcomes across all levels. After accounting for these variations in the cross-classified multilevel model framework, we evaluated the association between HF-WBI use and clinical and demographic factors.Our study included 79,747 women (74.0%) who underwent CF-WBI and 27,999 (26.0%) who received HF-WBI. HF-WBI adoption increased over time (2008-2017). Variability across radiation oncologists (ICC = 0.272, MOR = 2.88) was notably larger than geographic areas variability. Variability across CBSA (ICC = 0.097, MOR = 1.76) was the strongest among all the geographic levels. The variation in HF-WBI use was mainly attributed to physician-level variability (ICC=0.222, MOR=2.59) based on the cross-classified multilevel model. No substantial differences were found between young (aged 64 or younger with commercial health plans) and older patients (aged 65 or older with Medicare Advantage plans) in terms of both geographic and physician-level variations. After accounting for variability in radiation oncologists and CBSAs, older age, non-reception of chemotherapy, and several community-level factors, including longer distance from home to facility and higher community education level, were associated with a higher likelihood of HF-WBI use. These results may lend insights into potential facilitators/barriers to HF-WBI uptake. Future studies can further investigate the impact of the 2018 American Society for Radiation Oncology (ASTRO) guideline and the Covid-19 pandemic on HF-WBI use, which would illuminate potential improvements of healthcare practices. Citation Format: Yijia Sun, Loren Saulsberry, Chuanhong Liao, Donald Hedeker, Dezheng Huo. Geographic and physician-level variation in the use of hypofractionated radiotherapy for breast cancer in the U.S.: A cross-classified multilevel analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4846.

Geographic and Physician-Level Variation in the Use of Hypofractionated Radiation Therapy for Breast Cancer in the U.S.: A Cross-Classified Multilevel Analysis

We aimed to assess geographic and physician-level variation for hypofractionated whole-breast irradiation (HF-WBI) use for early-stage breast cancer patients in the United States. We further evaluated the association between HF-WBI use and demographic factors after accounting for these variations. We performed a retrospective study of early-stage breast cancer patients using private employer-sponsored insurance claims from 2008 to 2017. Patients were clustered according to geographic level and by radiation oncologist. Bayesian cross-classified multilevel logistic models were used to examine the geographic heterogeneity and variation of radiation oncologists simultaneously. Intracluster correlation coefficient (ICC) and median odds ratios (MOR) were calculated to quantify the variation at different levels. We also used the cross-classified model to identify patient demographic factors associated with receiving HF-WBI. The study included 79,747 women (74.0%) who received conventionally fractionated whole-breast irradiation (CF-WBI) and 27,999 women (26.0%) who underwent HF-WBI. HF-WBI adoption increased significantly across time (2008-2017). The variation in HF-WBI utilization was attributed mostly to physician-level variability (MOR = 2.59). The variability of HF-WBI utilization across core-based statistical areas (CBSAs) (MOR = 1.55) was found to be the strongest among all geographic classifications. After accounting for variability in both CBSAs and radiation oncologists, age, receiving chemotherapy, and several community-level factors, including distance from home to facility, community education level, and racial composition, were found to be associated with HF-WBI utilization. This study demonstrated geographic and physician-level heterogeneity in the use of HF-WBI among early-stage breast cancer patients. HF-WBI utilization was also found to be associated with patient and community-level characteristics. Given observed physician-level variability, intervention through continuing medical education could help doctors to better understand the advantages of HF-WBI and promote the adoption of HF-WBI in the U.S. Influence of physician-level characteristics on HF-WBI utilization merits further study.

Multilevel and general linear modeling of weather and time effects on the emotional and behavioral states of children with profound intellectual and multiple disabilities.

Eliciting the emotional and behavioral states of children with severe or profound intellectual disabilities (IDs) and profound intellectual and multiple disabilities (PIMD) due to their complex and atypical developmental trajectories has become increasingly elusive. It is evident that the environment, influenced by weather conditions and time of the day, plays a pivotal role in molding children's behaviors, emotions, and interactions. This underscores the significance of the environment as a critical factor in exploring the communication dynamics of children with PIMD/IDs. Over five months during fall and winter seasons, we conducted 105 video-recorded sessions with 20 children aged 8 to 16 with PIMD/IDs. These sessions aimed to capture the emotional and behavioral states interpreted by caregivers while simultaneously collecting indoor and outdoor weather indices, location, and time data. Using cross-classified multilevel and general linear models adjusted for individual characteristics and location variability with subsequent simple slope analyses, we examined the main and seasonal interaction effects of indoor and outdoor weather indices and time of the day on the emotional and behavioral states of children with PIMD/IDs. The models revealed that higher atmospheric pressure (atm), indicative of pleasant and favorable weather conditions, was associated with increased engagement (indoor: p < 0.01; outdoor: p < 0.01) and interest (outdoor: p < 0.01) behaviors. In contrast, engagement levels decreased before lunchtime (p < 0.01; p < 0.001), and inclement or unstable weather conditions characterized by low-pressure systems (p < 0.05) and stronger wind speed (p < 0.05) led to more refusal or disagreement. During winter, children displayed significantly more agreement with their caregivers (p < 0.001). Interestingly, they also engaged more on cloudy days (p < 0.05). Furthermore, simple slope analyses revealed that high atm conditions in fall were linked to more engagement (p < 0.05) while humid conditions predicted more assent behaviors (p < 0.001). However, cloudy weather predicted less attentional focusing (p < 0.05) and interest (p < 0.01) behaviors in winter. This study confirms that fluctuations in weather indices, including seasonal changes and time of the day, can provide potential pathway indicators and supplement behavioral observations to elicit the behavioral states of children with PIMD/IDs. These findings highlight the importance of considering these factors when designing meaningful interactions and communication interventions for this population.

Disaggregating level-specific effects in cross-classified multilevel models.

In psychology and other fields, data often have a cross-classified structure, whereby observations are nested within multiple types of non-hierarchical clusters (e.g., repeated measures cross-classified by persons and stimuli). This paper discusses ways that, in cross-classified multilevel models, slopes of lower-level predictors can implicitly reflect an ambiguous blend of multiple effects (for instance, a purely observation-level effect as well as a unique between-cluster effect for each type of cluster). The possibility of conflating multiple effects of lower-level predictors is well recognized for non-cross-classified multilevel models, but has not been fully discussed or clarified for cross-classified contexts. Consequently, in published cross-classified modeling applications, this possibility is almost always ignored, and researchers routinely specify models that conflate multiple effects. In this paper, we show why this common practice can be problematic, and show how to disaggregate level-specific effects in cross-classified models. We provide a novel suite of options that include fully cluster-mean-centered, partially cluster-mean-centered, and contextual effect models, each of which provides a unique interpretation of model parameters. We further clarify how to avoid both fixed and random conflation, the latter of which is widely misunderstood even in non-cross-classified models. We provide simulation results showing the possible deleterious impact of such conflation in cross-classified models, and walk through pedagogical examples to illustrate the disaggregation of level-specific effects. We conclude by considering additional model complexities that can arise with cross-classification, providing guidance for researchers in choosing among model specifications, and describing newly available software to aid researchers who wish to disaggregate effects in practice.

The Use of Remote Consultations and Associated Factors in Rheumatology: A Large Retrospective Cohort Study of Follow-Up Consultations Before, During, and After COVID-19.

To investigate the use of remote consultations (RCs) and the influence of consultation, health care provider (HCP), and patient characteristics on the choice for remote or face-to-face consultation. A monocenter retrospective cohort study was conducted on follow-up consultations of patients with rheumatic diseases from January 1, 2019 to January 16, 2023, using data from electronic health records. Trends in the proportion of RCs before, during, and after COVID-19 were studied. Cross-classified multilevel logistic regression models were built to account for clustering of consultations (level 1) within both patients and HCPs (level 2). The influence of consultation, patient, and HCP characteristics on the type of consultation was assessed. 157,028 consultations of 30,215 unique patients seen by 64 HCPs were included in the data set. After an initial sharp increase in RC use at the beginning of the COVID-19 pandemic, the proportion of RCs decreased toward a seemingly steady state at around 30%. 90% of the variance in the use of RCs can be attributed to the consultation level, whereas 4% and 6% can be attributed to the patient and HCP level. Longer consultation durations and time since last consultation decreased the odds for a RC, as did higher patient age, shared care, and longer disease duration. Higher travel distance, consultation density, and patient digital access increased the odds for a RC. The COVID pandemic resulted in a structural increase in the use of RCs. Although several patient characteristics are associated with the type of consultation, most variance resulted from consultation characteristics compared with patients and HCPs.

Fieldworker effects on quality of data collected on sensitive questions in National Family Health Surveys: An analysis based on intimate partner violence in India

National Family Health Survey (NFHS) has played a pivotal role in formulating policies and programs by providing nationally representative data on a wide range of monitoring and impact evaluation indicators in population, health and nutrition. However, due to measurement errors resulting in misreporting, the collection of accurate data on sensitive issues in sample surveys has always been a matter of concern. This study examines the fieldworker effect on the reporting of physical, sexual, and emotional Intimate Partner Violence (IPV) using fifth round of NFHS (2019-21) data in India. The cross-classified multi-level model was used to examine the fieldworker's effect on the reporting of IPV. The fieldworker effect accounted for around 32% of total variation in the reporting of intimate partner violence. The fieldworker's effect varied from 26% to 41 % for physical violence, 29% to 33% for emotional IPV and 30%–36% for sexual IPV. It was observed that variation due to fieldworker for non-sensitive outcomes was negligible.Of total variation, only 1.6% for information related to ever attending school, 4.8% for ever given birth, 5% for currently pregnant and 8.5% for information on ever terminated pregnancy was being explained by the fieldworker. Our results indicate a significant fieldworker influence on the likelihood of reporting intimate partner violence, underlining the need for an increased understanding of the impact of fieldworkers on data outputs, especially—but not exclusively—when queries contain delicate or stigmatized themes. This study highlights the importance of providing extra guidance and special training to the fieldworkers when collecting sensitive information related to IPV.

Time trends in associations between neighbourhood and school characteristics and mental health problems among Dutch adolescents

We investigated trends in associations between physical and social neighbourhood and school characteristics and adolescent mental health problems between 2005 and 2017. Nationally representative, repeated cross-sectional data collected in the Netherlands among primary (N = 5,871) and secondary school students (N = 20,778) were analysed through cross-classified multilevel models. Hardly any evidence was found for over-time changes in associations between neighbourhood and school characteristics and adolescent mental health problems. Findings showed that for both groups of students, only social characteristics within the two contexts were associated with adolescent mental health problems. For secondary school students, school effects were larger than neighbourhood effects, while the opposite was true for primary school students. Specifically, primary school students residing in more socially fragmented or lower socioeconomic status (SES) neighbourhoods, and lower SES schools, reported more conduct problems and peer relationship problems. For secondary school students, only the SES of the neighbourhood and the school was associated with all four aspects of mental health problems. Remarkably, the direction of the associations between neighbourhood/ school SES and adolescent mental health problems varied across the different mental health outcomes. More research is warranted to replicate our findings.

Solitary confinement and the well-being of people in prison

BackgroundSolitary confinement and mental well-being has been researched extensively, with a significant increase in studies over the last ten years. These recent studies produce mixed evidence for whether placement in solitary confinement is associated with psychological distress. We advance our understanding of these relationships in two critical ways. First, we conduct both between- and within-person analyses within the same data to better understand the relationship of solitary confinement and mental well-being relative to the well-being of people in less restrictive prison settings. Second, we ask the men in our sample questions about their personality style, coping strategies, and interactions with staff, which allows us to explore how individual characteristics and prison experiences matter, alongside isolation, in understanding mental well-being. MethodsWe gather data from interviews at three time points with 122 men in solitary confinement and 204 men in other conditions of confinement in Arizona from 2017 to 2019. We merge these interview data with administrative data on study sample and population sample to include critical measures such as mental health score, risk level, and visitation status. Our interviews contain a Global Severity Index (GSI), created from 90 self-reported psychopathological symptoms experienced, that we use to assess well-being. We estimate cross-classified multilevel models to assess between-person differences and within-person change in well-being over time. ResultsThere was a small relationship between solitary confinement and worsening well-bring (longitudinal, within-person) and a small relationship between solitary confinement and worse well-being (cross-sectional, between-person), with this between-person association reduced significantly upon inclusion of additional individual characteristics and prison experiences. ConclusionsOur results suggest that the incarceration experience, including conditions of confinement, is associated with mental well-being in different ways for different people. We believe that collective confinement and well-being could receive the same scholarly attention and public concern as solitary confinement.

Adolescent individual, school, and neighborhood influences on young adult diabetes risk.

Using data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), this study examines the association between adolescent school and neighborhood contexts and the likelihood of diabetes in young adulthood. We apply cross-classified multi-level modeling (CCMM) techniques to examine the simultaneous influence of non-nested school and neighborhood contexts as well as individual, school, and neighborhood-level factors (N=14,041 participants from 128 schools, 1933 neighborhoods). Our findings suggest that individual-level factors are most associated with young adult diabetes, with small contributions from school and neighborhood factors and a small proportion of the variation explained by school and neighborhood contexts.

Disparities in healthcare utilization by insurance status among patients with symptomatic peripheral artery disease

BackgroundPeripheral artery disease (PAD) is a common circulatory disorder associated with increased hospitalizations and significant health care-related expenditures. Among patients with PAD, insurance status is an important determinant of health care utilization, treatment of disease, and treatment outcomes. However, little is known about PAD-costs differences across different insurance providers. In this study we examined possible disparities in length of stay and total charge of inpatient hospitalizations among patients with PAD by insurance type.MethodsWe conducted a cross-sectional analysis of length of stay and total charge by insurance provider for all hospitalizations for individuals with PAD in South Carolina (2010–2018). Cross-classified multilevel modeling was applied to account for the non-nested hierarchical structure of the data, with county and hospital included as random effects. Analyses were adjusted for patient age, race/ethnicity, county, year of admission, admission type, all-patient refined diagnostic groups, and Charlson comorbidity index.ResultsAmong 385,018 hospitalizations for individuals with PAD in South Carolina, the median length of stay was 4 days (IQR: 5) and the median total charge of hospitalization was $43,232 (IQR: $52,405). Length of stay and total charge varied significantly by insurance provider. Medicare patients had increased length of stay (IRR = 1.08, 95 CI%: 1.07, 1.09) and higher total charges (β: 0.012, 95% CI: 0.007, 0.178) than patients with private insurance. Medicaid patients also had increased length of stay (IRR = 1.26, 95% CI: 1.24,1.28) but had lower total charges (β: -0.022, 95% CI: -0.003. -0.015) than patients with private insurance.ConclusionsInsurance status was associated with inpatient length of stay and total charges in patients with PAD. It is essential that Medicare and Medicaid individuals with PAD receive proper management and care of their PAD, particularly in the primary care settings, to prevent hospitalizations and reduce the excess burden on these patients.

Adolescent alcohol use: use of social network analysis and cross-classified multilevel modeling to examine peer group, school, and neighborhood-level influences

ABSTRACT Background: Neighborhood-, school-, and peer-contexts play an important role in adolescent alcohol use behaviors. Methodological advances permit simultaneous modeling of these contexts to understand their relative and joint importance. Few empirical studies include these contexts, and studies that do typically: examine each context separately; include contexts for the sole purpose of accounting for clustering in the data; or do not disaggregate by sex. Objectives: This study takes an eco-epidemiologic approach to examine the role of socio-contextual contributions to variance in adolescent alcohol use. The primary parameters of interest are therefore variance rather than beta parameters (i.e. random rather than fixed effects). Sex-stratified models are also used to understand how each context may matter differently for male and female adolescents. Method: Data come from the National Longitudinal Study of Adolescent to Adult Health (n = 8,534 females, n = 8,102 males). We conduct social network analysis and traditional and cross-classified multilevel models (CCMM) in the full and sex-disaggregated samples. Results: In final CCMM, peer groups, schools, and neighborhoods contributed 10.5%, 10.8%, and 0.4%, respectively, to total variation in adolescent alcohol use. Results do not differ widely by gender. Conclusions: Peer groups and schools emerge as more salient contributing contexts relative to neighborhoods in adolescent alcohol use for males and females. These findings have both methodological and practical implications. Multilevel modeling can model contexts simultaneously to prevent the overestimation of variance in youth alcohol use explained by each context. Primary prevention strategies addressing youth alcohol use should focus on schools and peer networks.

Changing times and subjective well-being in urban China 2003–2013: An age-period-cohort approach

This paper analyzes the intersection of individual lives and historical context by examining how cohort membership, historical conditions, and individual maturation influence subjective well-being in urban China. We use cross-classified multilevel models and repeated measures of happiness from seven waves of the Chinese General Social Survey (CGSS 2003–2013, N = 43,308). The results indicate that individuals born between 1956 and 1961 experienced setbacks at various pivotal moments throughout their life, including education, employment, economic stability, and social connections, and this cohort reports a lower overall sense of happiness when compared to other cohorts. The effect of aging on happiness comprises a U-shaped pattern; the middle-aged are the least happy. We observe an upward trend in happiness from 2003 to 2013. These results are confirmed by using subjective socioeconomic status (SES) as an alternative measure of well-being from CGSS 2003 and CGSS 2005 (N = 11,992). This paper contributes to studies of market transition by identifying the birth cohort as an important mechanism of inequality. It also augments the life-course paradigm by highlighting the significance of timing when individual lives intersect with historical context.

Answering it or skipping it: predicting item nonresponse in school self-evaluation questionnaires

ABSTRACT In the process of school self-evaluation (SSE), teachers are often asked to provide information on the school’s functioning by completing questionnaires. However, respondents can leave one item or a series of items unanswered, after which they continue completing the questionnaire. This phenomenon of item nonresponse is not necessarily problematic if it occurs randomly. This study examines to what extent item nonresponse depends on respondents’ motivation to fill in the SSE questionnaire, their tendency towards socially desirable responses, the evaluation perspective on the SSE, the item design, and the construct that the item aims to shed light on. This study reports on an experimental study with 376 respondents who completed a questionnaire in an authentic SSE setting. Cross-classified multilevel modelling identified that respondents’ autonomous motivation predicts item nonresponse. Also, the evaluation perspective on SSE, item design, and the construct the item tends to capture all affect the probability of item nonresponse.

Growing up together: Differences between siblings in the development of compliance separating within-family and between-family effects.

This study applies a within-family, age-snapshot design to investigate differences between siblings in the development of compliance during the preschool years by disaggregating situational, within-family, and between-family effects. The aim of the study was to investigate the relation between sibling differences in compliance and the within-family factors birth order and differential parenting, as well as interactions between these factors. Using observational data of 311 Dutch families (self-identified as culturally Dutch) with 2 children when each child was 3 and 4 years old (firstborns: 36.2 months old; SD = 3.6; 48% girls, second-borns (2 years later): 36.67 months old; SD = .62; 47% girls) and both parents. Three-level cross-classified multilevel models showed main effects of observed sibling noncompliance and differential verbal discipline on noncompliance. In addition, second-born children were more compliant than their firstborn siblings, but only when the firstborn was disciplined physically more often than his/her younger sibling. The results provide evidence that birth-order effects may partially be explained by differential parenting and suggest that differences between siblings cannot be fully understood without taking into account the influence of both direct and indirect sibling effects. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Study on the socioeconomic and climatic effects of forest fire incidence in the Changbai Mountain area based on a cross-classified multilevel model

The occurrence of forest fires is determined by fuel, climate and ignition sources at different temporal and spatial scales. However, most analyses are performed only on a single scale, and few comprehensive statistical analyses elaborate on the cross-scale interaction of fire drivers. Understanding the differential effects of socioeconomic and climatic factors on forest fire incidence across different administrative and climatic scales can provide new information for wildfire studies. In this study, we applied a cross-classified multilevel model with forest fire incidence data derived from Moderate Resolution Imaging Spectroradiometer products (MODIS 14A1) to explore the relationship between the spatial distribution of fire incidence and socioeconomic and climatic factors at different levels and to estimate the effects of these drivers on forest fire incidence. Our results showed that the density of impervious surfaces, density of cropland, mean monthly precipitation, mean monthly temperature, density of primary gross domestic product, annual monthly average relative humidity, and annual monthly average precipitation at the county level, prefecture-level city and climatic levels had significant multilevel associations with forest fire incidence in the Changbai Mountain area. These findings will effectively support the development of forest fire administrative policies for specific regions.