A Simple-to-Use R Package for Mimicking Study Data by Simulations.

BACKGROUND: Data protection policies might prohibit the transfer of existing study data to interested research groups. To overcome legal restrictions, simulated data can be transferred that mimic the structure but are different from the existing study data. OBJECTIVES: The aim of this work is to introduce the simple-to-use R package Mock Data Generation (modgo) that may be used for simulating data from existing study data for continuous, ordinal categorical, and dichotomous variables. METHODS: The core is to combine rank inverse normal transformation with the calculation of a correlation matrix for all variables. Data can then be simulated from a multivariate normal and transferred back to the original scale of the variables. Unique features of modgo are that it allows to change the correlation between variables, to perform perturbation analysis, to handle multicenter data, and to change inclusion/exclusion criteria by selecting specific values of one or a set of variables. Simulation studies on real data demonstrate the validity and flexibility of modgo. RESULTS: modgo mimicked the structure of the original study data. Results of modgo were similar with those from two other existing packages in standard simulation scenarios. modgo's flexibility was demonstrated on several expansions. CONCLUSION: The R package modgo is useful when existing study data may not be shared. Its perturbation expansion permits to simulate truly anonymized subjects. The expansion to multicenter studies can be used for validating prediction models. Additional expansions can support the unraveling of associations even in large study data and can be useful in power calculations.

Determinants of verbal fluency trajectories among older adults from the English Longitudinal Study of Aging.

BACKGROUND: Prevalence of dementia and cognitive impairment increase creating the need for identifying modifiable risk factors to reduce their burden. The aim of this study was to identify latent groups following similar trajectories in cognitive performance assessed with the verbal fluency test, as well as their determinants. METHODS: Data from English Longitudinal Study of Aging (ELSA) were studied. Latent groups of similar course through a 6-year period in the outcome variable (verbal fluency) were investigated, along with their determinants, using Group Based Trajectory Modeling (GBTM). RESULTS: Four latent groups of verbal fluency trajectories were revealed. Education was the strongest predictor for a favorable trajectory, while cardiovascular disease and depression symptoms were associated with lower within each trajectory. CONCLUSION: Cardiovascular diseases and depressive symptoms are associated with a worse course of verbal fluency through aging, implying that they might serve as targets for interventions to prevent cognitive decline in the aging population. Contrarily, higher level of education is associated with a more favorable course through aging.

Determinants of Processing Speed Trajectories among Middle Aged or Older Adults, and Their Association with Chronic Illnesses: The English Longitudinal Study of Aging.

The aim of this study was to identify latent groups of similar trajectories in processing speed through aging, as well as factors that are associated with these trajectories. In the context of the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) project, data from the English Longitudinal Study of Aging (ELSA) (n = 12099) were analyzed. Latent groups of similar trajectories in the processing scores as well as their predictors and covariates were investigated, using group-based trajectory models (GBTM). The coefficient estimates for potential group predictors correspond to parameters of multinomial logit functions that are integrated in the model. Potential predictors included sex, level of education, marital status, level of household wealth, level of physical activity, and history of smoking, while time-varying covariates included incidence of cardiovascular disease (CVD), diabetes mellitus, depressive symptoms, and sleep disturbances. Four trajectories were identified and named after their baseline scores and shapes: High (4.4%), Middle/Stable (31.5%), Low/Stable (44.5%), and Low Decline (19.6%). Female sex, higher levels of education, mild level of physical activity, having been married, and higher level of wealth were associated with a higher probability of belonging to any of the higher groups compared to the Low/Decline that was set as reference, while presence of CVD, diabetes mellitus, and depressive symptoms were associated with lower processing speed scores within most trajectories. All the aforementioned factors might be valid targets for interventions to reduce the burden of age-related cognitive impairment.