Latent class analysis was accurate but sensitive in data simulations

Objectives: Latent class methods are increasingly being used in analysis of developmental trajectories. A recent simulation study by Twisk and Hoekstra (2012) suggested caution in use of these methods because they failed to accurately identify developmental patterns that had been artificially imposed on a real data set. This article tests whether existing developmental patterns within the data set used might have obscured the imposed patterns.<p></p> Study Design and Setting: Data were simulated to match the latent class pattern in the previous article, but with varying levels of randomly generated variance, rather than variance carried over from a real data set. Latent class analysis (LCA) was then used to see if the latent class structure could be accurately identified.<p></p> Results: LCA performed very well at identifying the simulated latent class structure, even when the level of variance was similar to that reported in the previous study, although misclassification began to be more problematic with considerably higher levels of variance.<p></p> Conclusion: The failure of LCA to replicate the imposed patterns in the previous study may have been because it was sensitive enough to detect residual patterns of population heterogeneity within the altered data. LCA performs well at classifying developmental trajectories.<p></p&gt

First year mathematics undergraduates’ settled images of tangent line

This article was published in the serial, The Journal of Mathematical Behavior [© Elsevier]. The definitive version is available at: http://www.sciencedirect.com/science/article/pii/S0732312310000556This study concerns 182 first year mathematics undergraduates’ perspectives on the tangent line of function graph in the light of a previous study on Year 12 pupils’ perspectives. The aim was the investigation of tangency images that settle after undergraduates’ distancing from the notion for a few months and after their participation in university admission examination. To this end we related the performances of the undergraduates and the pupils in the same questions of a questionnaire; we classified the undergraduates in distinct groups through Latent Class Analysis; and, we examined this classification according to the Analytical Local, Geometrical Global and Intermediate Local perspectives on tangency we had identified among pupils. The findings suggest that more undergraduates than pupils demonstrated intermediate perspectives on tangency. Also, the undergraduates’ settled images were influenced by persistent images about tangency and their prior experience in the context of preparation for and participation in the examination

On growth curves and mixture models

The multilevel model of change and the latent growth model are flexible means to describe all sorts of population heterogeneity with respect to growth and development, including the presence of sub-populations. The growth mixture model is a natural extension of these models. It comes at hand when information about sub-populations is missing and researchers nevertheless want to retrieve developmental trajectories from sub-populations. We argue that researchers have to make rather strong assumptions about the sub-populations or latent trajectory classes in order to retrieve existing population differences. A simulated example is discussed, showing that a sample of repeated measures drawn from two sub-populations easily leads to the mistaken inference of three sub-populations, when assumptions are not met. The merits of methodological advises on this issue are discussed. It is concluded that growth mixture models should be used with understanding, and offer no free way to growth patterns in unknown sub-populations. Copyright © 2006 John Wiley & Sons, Ltd

Thurstonian Scaling of Compositional Questionnaire Data

To prevent response biases, personality questionnaires may use comparative response formats. These include forced choice, where respondents choose among a number of items, and quantitative comparisons, where respondents indicate the extent to which items are preferred to each other. The present article extends Thurstonian modeling of binary choice data (Brown & Maydeu-Olivares, 2011a) to “proportion-of-total” (compositional) formats. Following Aitchison (1982), compositional item data are transformed into log-ratios, conceptualized as differences of latent item utilities. The mean and covariance structure of the log-ratios is modelled using Confirmatory Factor Analysis (CFA), where the item utilities are first-order factors, and personal attributes measured by a questionnaire are second-order factors. A simulation study with two sample sizes, N=300 and N=1000, shows that the method provides very good recovery of true parameters and near-nominal rejection rates. The approach is illustrated with empirical data from N=317 students, comparing model parameters obtained with compositional and Likert scale versions of a Big Five measure. The results show that the proposed model successfully captures the latent structures and person scores on the measured traits

Trajectories of university adjustment in the United Kingdom: Emotion management and emotional self-efficacy protect against initial poor adjustment

Little is known about individual differences in the pattern of university adjustment. This study explored longitudinal associations between emotional self-efficacy, emotion management, university adjustment, and academic achievement in a sample of first year undergraduates in the United Kingdom (N=331). Students completed measures of adjustment to university at three points during their first year at university. Latent Growth Mixture Modeling identified four trajectories of adjustment: (1) low, stable adjustment, (2) medium, stable adjustment, (3) high, stable adjustment, and (4) low, increasing adjustment. Membership of the low, stable adjustment group was predicted by low emotional self-efficacy and low emotion management scores, measured at entry into university. This group also had increased odds of poor academic achievement, even when grade at entry to university was controlled. Students who increased in adjustment had high levels of emotion management and emotional self-efficacy, which helped adaptation. These findings have implications for intervention

The transmission of nosocomial pathogens in an intensive care unit: a space–time clustering and structural equation modelling approach

We investigated the incidence of cases of nosocomial pathogens and risk factors in an intensive treatment unit ward to determine if the number of cases is dependent on location of patients and the colonization/infection history of the ward. A clustering approach method was developed to investigate the patterns of spread of cases through time for five microorganisms [methicillin-resistant Staphylococcus aureus (MRSA), Acinetobacter spp., Klebsiella spp., Candida spp., and Pseudomonas aeruginosa] using hospital microbiological monitoring data and ward records of patient-bed use. Cases of colonization/infection by MRSA, Candida and Pseudomonas were clustered in beds and through time while cases of Klebsiella and Acinetobacter were not. We used structural equation modelling to analyse interacting risk factors and the potential pathways of transmission in the ward. Prior nurse contact with colonized/infected patients, mediated by the number of patient-bed movements, were important predictors for all cases, except for those of Pseudomonas. General health and invasive surgery were significant predictors of cases of Candida and Klebsiella. We suggest that isolation and bed movement as a strategy to manage MRSA infections is likely to impact upon the incidence of cases of other opportunist pathogen

The Impact of Covariance Misspecification in Multivariate Gaussian Mixtures on Estimation and Inference: An Application to Longitudinal Modeling

Multivariate Gaussian mixtures are a class of models that provide a flexible parametric approach for the representation of heterogeneous multivariate outcomes. When the outcome is a vector of repeated measurements taken on the same subject, there is often inherent dependence between observations. However, a common covariance assumption is conditional independence---that is, given the mixture component label, the outcomes for subjects are independent. In this paper, we study, through asymptotic bias calculations and simulation, the impact of covariance misspecification in multivariate Gaussian mixtures. Although maximum likelihood estimators of regression and mixing probability parameters are not consistent under misspecification, they have little asymptotic bias when mixture components are well-separated or if the assumed correlation is close to the truth even when the covariance is misspecified. We also present a robust standard error estimator and show that it outperforms conventional estimators in simulations and can indicate the model is misspecified. Body mass index data from a national longitudinal study is used to demonstrate the effects of misspecification on potential inferences made in practice

Dataset regarding access to information for persons with disabilities in Serbia

Access to information is key for improving the position of persons with disabilities in society. Familiarity with state regulations regarding access to information could be influenced by communication with state authorities concerning the rights of persons with disabilities, especially access to information. Familiarity with these regulations and the specified communication with state authorities might be affected by a number of background variables, such as age and education completed. To clarify relations among these variables, which would enable state authorities and other relevant institutions to define and implement policies that might improve matters, there is a need to prepare and analyze appropriate datasets concerning them. This paper describes such a dataset, preliminary in nature, obtained from answers to part of a questionnaire administered to persons with disabilities living in Serbia. Persons with innate or acquired physical and/or sensory disability were included in the research. This dataset contains raw data of nine variables, as well as analyzed data of ten variables derived from most of the raw data. Besides correlative analyses, the dataset was previously analyzed using PLS (partial least squares) path modeling. To reuse the dataset, a path model with Bayesian estimations may be applied, whose outcomes for different model priors (prior distributions) may be compared to those of the PLS path modeling. The dataset also contains data of two variables that may be included in further research

Psychological distress in mid-life: evidence from the 1958 and 1970 British birth cohorts

BACKGROUND: This paper addresses the levels of psychological distress experienced at age 42 years by men and women born in 1958 and 1970. Comparing these cohorts born 12 years apart, we ask whether psychological distress has increased, and, if so, whether this increase can be explained by differences in their childhood conditions. METHOD: Data were utilized from two well-known population-based birth cohorts, the National Child Development Study and the 1970 British Cohort Study. Latent variable models and causal mediation methods were employed. RESULTS: After establishing the measurement equivalence of psychological distress in the two cohorts we found that men and women born in 1970 reported higher levels of psychological distress compared with those born in 1958. These differences were more pronounced in men (b = 0.314, 95% confidence interval 0.252-0.375), with the magnitude of the effect being twice as strong compared with women (b = 0.147, 95% confidence interval 0.076-0.218). The effect of all hypothesized early-life mediators in explaining these differences was modest. CONCLUSIONS: Our findings have implications for public health policy, indicating a higher average level of psychological distress among a cohort born in 1970 compared with a generation born 12 years earlier. Due to increases in life expectancy, more recently born cohorts are expected to live longer, which implies - if such differences persist - that they are likely to spend more years with mental health-related morbidity compared with earlier-born cohorts

Language skills, peer rejection, and the development of externalizing behavior from kindergarten to fourth grade

Background: Children with poorer language skills are more likely to show externalizing behavior problems, as well as to become rejected by their peers. Peer rejection has also been found to affect the development of externalizing behavior. This study explored the role of peer rejection in the link between language skills and the development of externalizing behavior. Methods: Six hundred and fifteen (615) children were followed from kindergarten to grade 4. Receptive language skills were measured with the Peabody Picture Vocabulary Test in grade 2. Teachers reported externalizing behavior and peer reports of social rejection were measured annually. Results: Children with poorer receptive language skills showed increasing externalizing behavior, while children with better receptive language skills showed decreases in externalizing behavior. Children with poorer receptive language skills experienced peer rejection most frequently. The link between receptive language skills and the development of externalizing behavior was mediated by the development of peer rejection. Findings suggested that this mediational link applied mostly to boys. Conclusion: Children with poorer language skills are at increased risk of becoming rejected by mainstream peers, which adds to the development of externalizing behavior. © 2010 The Authors. Journal of Child Psychology and Psychiatry. © 2010 Association for Child and Adolescent Mental Health