Unlinked vital events in census-based longitudinal studies can bias subsequent analysis

Objective: To examine the potential biases arising from the nonlinkage of census records and vital events in longitudinal studies.
Study Design and Setting: A total of 56,396 deaths of residents of Northern Ireland in the 4 years after the 2001 Census were linked to the 2001 Census records. The characteristics of matched and nonmatched death records were compared using multivariate logistic regression. Subject attributes were as recorded on the death certificate.
Results: In total, 3,392 (6.0%) deaths could not be linked to a census record. Linkage rates were lowest in young adults, males, the unmarried, people living in communal establishments, or living in areas that were more deprived or had recorded low census enumeration. For those aged less than 65 years at census, this linkage would exclude from analysis 20.2% of suicides and 19.7% of deaths by external causes.
Conclusion: The nonlinkage of census and death records is a combination of nonenumeration at census and deficient information about the deceased recorded at the time of death. Unmatched individuals may have been more disadvantaged or socially isolated, and analysis based on the linked data set may therefore show some bias and perhaps understate true social gradients.

Longitudinal studies into science learning - methodological issues

The Gold Standard for education research promotes randomized controlled trials (RCTs) that can produce generalizable knowledge claims across similar problems and situations. Unfortunately, the Gold Standard does not fully recognize the need for developmental research to better understand the problem space, formulate theory and approaches to teaching and learning, and formulate and pursue associated research questions. This developmental research has been a precursor to the development of interventions together with the necessary instrumentation and technologies required to fully investigate these through the more formal evaluative processes imagined by the Gold Standard. This chapter focuses on longitudinal studies that cover a continuum from such developmental research to research that uses control-experimental features to evaluate interventions. These studies attend to a set of issues dealing with  developmental progressions and learning trajectories that require  investigation over an extended period of time. It will be argued that
these longitudinal studies of a variety of methodological types represent quality research in that rigorous design and implementation produce  evidence-based claims. The chapter examines the nature of the relationship between evidence and claims in these studies, to show the possibility of building in control features every bit as strong as those in classic Gold Standard designs. Further, it will be argued that, given the complexity of learning pathways, a simplistic interpretation of RCTs conducted over the shorter term can be misleading in terms of both internal and external validity claims.

The effect of peer influence and selection processes on adolescent alcohol use : a systematic review of longitudinal studies.

Adolescent alcohol use remains an important public health concern. One of the most salient and consistent predictors for drinking behaviour among young people is peer influence. A systematic review of longitudinal studies that examined the effect of peer influence on adolescent alcohol use between January 1997 and February 2011 is presented. Twenty-two studies fulfilled inclusion criteria and were reviewed. All but one study confirmed affiliation with alcohol-using or deviant peers as prospective predictors for the development of adolescent alcohol use. Findings revealed that existing longitudinal studies that have used multivariate analytic techniques to segregate peer influence (whereby adolescents start drinking after exposure to alcohol-using friends) and peer selection (whereby adolescents that start drinking without alcohol-using friends subsequently seek out drinking peers) effects consistently report significant peer influence effects. However, studies are unable to elucidate the relative contribution and developmental sequence of peer influence and selection. Existing research is synthesised to model the developmental influence of peer processes on adolescent alcohol use. Future research directions are recommended to inform better designed investigations that can lead to more effective endeavours to address peer processes in prevention efforts.

The Maltreatment-Offending Association: a systematic review of the methodological features of prospective and longitudinal studies

Although the association between childhood maltreatment and the subsequent development of offending behavior is well documented, the association does not necessarily reflect a causal relationship. This paper provides a systematic review of prospective and longitudinal studies using official records of maltreatment to gain insights into the extent to which methodological variations are likely to influence the conclusions drawn about the likely relationship between maltreatment and offending. Sixty-two original studies met the inclusion criteria. These studies were assessed according to a set of seven methodological criteria: (1) inclusion of comparison groups, (2) the use of statistical controls, (3) valid outcome measures, (4) operationalization of maltreatment, (5) proper temporal order of associations, (6) data relating to unsubstantiated maltreatment, and (7) consideration of mediating and moderating factors. The strength of evidence in support of the maltreatment-offending association was influenced by a number of methodological factors. Despite the increasing sophistication of studies, there is a need to be mindful of how these factors are taken into account in future research in order to gain a deeper understanding of the adverse consequences of maltreatment and how this might influence outcomes and inform interventions.

Transforming the SF-36 to account for death in longitudinal studies with three-year follow-up

BACKGROUND: Analyses of longitudinal health-related quality of life data often exclude participants who die, which limits the generalizability of the results. Methods to incorporate death as a valid score in the Medical Outcomes Study Short-Form (SF-36) have been suggested but need to be evaluated in other populations. OBJECTIVES: We sought to apply a method of transforming the SF-36 Physical Component Score (PCS) to include death. A transformation to estimate the probability of being "healthy" in 3 years, based on the current PCS value, will be developed and validated. SUBJECTS: Women in the Australian Longitudinal Study on Women's Health (ALSWH), ages 70-75 years at Survey 1 in 1996 (n = 12,432), were followed-up at 3 yearly intervals for 6 years. RESULTS: The transformation derived from the ALSWH data provides evidence that the methodology for transforming the PCS to account for deaths is sound. The 3-year equation provided good estimates of the probability of being healthy in 3 years and the method allowed deaths to be included in an analysis of changes in health over time. CONCLUSIONS: For longitudinal studies involving the SF-36 in which subjects have died, we support the recommendation that both the PCS and its transformed value which includes deaths should be analyzed to examine the influence of deaths on the study conclusions. Using study data to derive empirical parameters for the transformations may be appropriate for studies with follow-up intervals of other lengths.

Systematic review of the survival rate and the incidence of biological, technical, and aesthetic complications of single crowns on implants reported in longitudinal studies with a mean follow-up of 5 years

To assess the 5-year survival of implant-supported single crowns (SCs) and to describe the incidence of biological, technical, and aesthetic complications. The focused question was: What is the survival rate of implants supporting single crowns and implant-supported crowns with a mean follow-up of 5 years and to which extent do biological, technical, and aesthetic complications occur?

Estimation with Interval Censored Data in Longitudinal Studies

In biostatistical applications interest often focuses on the estimation of the distribution of a time-until-event variable T. If one observes whether or not T exceeds an observed monitoring time at a random number of monitoring times, then the data structure is called interval censored data. We extend this data structure by allowing the presence of a possibly time-dependent covariate process that is observed until end of follow up. If one only assumes that the censoring mechanism satisfies coarsening at random, then, by the curve of dimensionality, typically no regular estimators will exist. To fight the curse of dimensionality we follow the approach of Robins and Rotnitzky (1992) by modeling parameters of the censoring mechanism. We model the right-censoring mechanism by modeling the hazard of the follow up time, conditional on T and the covariate process. For the monitoring mechanism we avoid modeling the joint distribution of the monitoring times by only modeling a univariate hazard of the pooled monitoring times, conditional on the follow up time, T, and the covariates process, which can be estimated by treating the pooled sample of monitoring times as i.i.d. In particular, it is assumed that the monitoring times and the right-censoring times only depend on T through the observed covariate process. We introduce inverse probability of censoring weighted (IPCW) estimator of the distribution of T and of smooth functionals thereof which are guaranteed to be consistent and asymptotically normal if we have available correctly specified semiparametric models for the two hazards of the censoring process. Furthermore, given such correctly specified models for these hazards of the censoring process, we propose a one-step estimator which will improve on the IPCW estimator if we correctly specify a lower-dimensional working model for the conditional distribution of T, given the covariate process, that remains consistent and asymptotically normal if this latter working model is misspecified. It is shown that the one-step estimator is efficient if each subject is at most monitored once and the working model contains the truth. In general, it is shown that the one-step estimator optimally uses the surrogate information if the working model contains the truth. It is not optimal in using the interval information provided by the current status indicators at the monitoring times, but simulations in Peterson, van der Laan (1997) show that the efficiency loss is small.

Disentangling the effects of low self-esteem and stressful events on depression: Findings from three longitudinal studies

Diathesis-stress models of depression suggest that low self-esteem and stressful events jointly influence the development of depressive affect. More specifically, the self-esteem buffering hypothesis states that, in the face of challenging life circumstances, individuals with low self-esteem are prone to depression because they lack sufficient coping resources, whereas those with high self-esteem are able to cope effectively and consequently avoid spiraling downward into depression. The authors used data from 3 longitudinal studies of adolescents and young adults, who were assessed 4 times over a 3-year period (Study 1; N = 359), 3 times over a 6-week period (Study 2; N = 249), and 4 times over a 6-year period (Study 3; N = 2,403). In all 3 studies, low self-esteem and stressful events independently predicted subsequent depression but did not interact in the prediction. Thus, the results did not support the self-esteem buffering hypothesis but suggest that low self-esteem and stressful events operate as independent risk factors for depression. In addition, the authors found evidence in all 3 studies that depression, but not low self-esteem, is reciprocally related to stressful events, suggesting that individuals high in depression are more inclined to subsequently experience stressful events.