Some Limits Using Random Slope Models to Measure Academic Growth

Wright, Daniel B.

doi:10.3389/feduc.2017.00058

Cited by 14 publications

(4 citation statements)

References 20 publications

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“…Results were similar when we applied LMMs to investigate the trajectories for every year separately ( Table 2 ). Furthermore, since only a few observations were available for each centenarian, we could not include random slopes in the LMMs, 51 such that we could not estimate the variability of the rates of decline between individual trajectories after study inclusion or during a specific year after study inclusion.…”

Section: Resultsmentioning

confidence: 99%

Association of Cognitive Function Trajectories in Centenarians With Postmortem Neuropathology, Physical Health, and Other Risk Factors for Cognitive Decline

et al. 2021

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IMPORTANCE Understanding mechanisms associated with prolonged cognitive health in combination with exceptional longevity might lead to approaches to enable successful aging. OBJECTIVE To investigate trajectories of cognitive functioning in centenarians across domains, and to examine the association of these trajectories with factors underlying cognitive reserve, physical health, and postmortem levels of Alzheimer disease (AD)-associated neuropathology. DESIGN, SETTING, AND PARTICIPANTS This cohort study used neuropsychological test data and postmortem neuropathological reports from Dutch centenarians who were drawn from the 100-plus Study between January 2013 and April 2019. Eligible participants self-reported being cognitively healthy, which was confirmed by a proxy. Data analysis was performed between June 2019 and June 2020. EXPOSURES Age, sex, APOE ε genotype, factors of cognitive reserve, physical health, and AD-associated neuropathology (ie, amyloid-β, neurofibrillary tangles, and neuritic plaques). MAIN OUTCOMES AND MEASURESIn annual visits (until death or until participation was no longer possible), centenarians underwent an extensive neuropsychological test battery, from which an mean z score of global cognition, memory, executive functions, verbal fluency, visuospatial functions, and attention/processing speed was calculated. Linear mixed models with a random intercept and time as independent variable were used to investigate cognitive trajectories, adjusted for sex, age, education, and vision and hearing capacities. In a second step, linear mixed models were used to associate cognitive trajectories with factors underlying cognitive reserve, physical health at baseline, and AD-associated neuropathology. RESULTSOf the 1023 centenarians approached, 340 were included in the study. We analyzed 330 centenarians for whom cognitive tests were available at baseline (239 [72.4%] women; median [interquartile range] age of 100.5 [100.2-101.7] years), with a mean (SD) follow-up duration of 1.6 (0.8) years. We observed no decline across investigated cognitive domains, with the exception of a slight decline in memory function (β, −0.10 SD per year; 95% CI, −0.14 to −0.05 SD; P < .001).

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Section: Resultsmentioning

confidence: 99%

Association of Cognitive Function Trajectories in Centenarians With Postmortem Neuropathology, Physical Health, and Other Risk Factors for Cognitive Decline

et al. 2021

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“…To achieve slopes that accurately represent the data, a large number of follow-ups for each person is required. More specifically, based on the work by Wright et al [59] to obtain estimated slopes that have a high correlation (> 0.8) with the true underlying slopes, 8 timepoints per person are needed. Therefore, participants were included in this analysis if they had at least 8 follow-up visits.…”

Section: Cognitive Changementioning

confidence: 99%

Subjective cognitive decline is a better marker for future cognitive decline in females than in males

et al. 2022

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Background The identification of biomarkers for early detection of Alzheimer’s disease (AD) is critical to the development of therapies and interventions targeted at symptom management and tracking the pathophysiology of disease. The endorsement of subjective cognitive decline (SCD) has emerged as a potential indicator of early change in cognitive status that may be predictive of future impairment at a time when measurable declines in neuropsychological performance cannot be detected. While there are numerous findings revealing sex differences in the prevalence of AD, there is a paucity of research examining sex differences in SCD. Therefore, the goal of this project was to determine if the relationship between the endorsement of SCD and future cognitive changes differ as a function of biological sex. Methods A sample of 3019 male and female healthy older adults (2188 without SCD, 831 with SCD), with a mean follow-up time of 5.7 years, were included from the Rush Alzheimer’s Disease Center Research Sharing Hub. Linear regressions were performed to determine group differences in baseline cognitive scores, while linear mixed-effects models were completed to determine group differences in the rate of cognitive change over time. Results Individuals endorsing SCD had significantly lower baseline cognitive scores and increased rates of decline in all cognitive domains compared to those without SCD. Males exhibited significantly lower scores in baseline performance in global cognition, episodic memory, and perceptual speed regardless of SCD classification. Females with SCD were found to decline at significantly faster rates than both males with SCD and males and females without SCD in all cognitive domains over a maximum 15-year follow-up period. Conclusions SCD is related to lower baseline cognitive performance and faster cognitive decline compared to those who do not endorse SCD. Females with SCD have the fastest rate of decline suggesting that SCD may be more predictive of future decline in females than in males. Targeted assessments of SCD may allow for the identification of individuals for inclusion in intervention trials, and other research studies, aiming to attenuate casual disease processes, which may ultimately aid in the mitigation of sex disparities in AD.

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“…Instead, we use restricted maximum likelihood (REML) to solve the system by an iterative procedure [13], as implemented in the lmer function in the lme4 package in R. The resulting model then has estimates of the slope coefficients for each gene (random effects), along with variances. In the formula used to specify the model to lmer, Y~1+conc+(1|gene)+(0+conc| gene), the fitting of the gene-dependent random effect parameters (intercepts and slopes) is intentionally decoupled, because we expect that the gene-specific interaction of the gene with the drug (slope) should be uncorrelated with the overall abundance of the gene in the library (intercept) [14], and this decoupling has been shown to produce more reliable estimates of random effect parameters when they are uncorrelated [15]. We are primarily interested in genes with negative slopes (i.e.…”

Section: Plos Onementioning

confidence: 99%

An improved statistical method to identify chemical-genetic interactions by exploiting concentration-dependence

et al. 2021

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Chemical-genetics (C-G) experiments can be used to identify interactions between inhibitory compounds and bacterial genes, potentially revealing the targets of drugs, or other functionally interacting genes and pathways. C-G experiments involve constructing a library of hypomorphic strains with essential genes that can be knocked-down, treating it with an inhibitory compound, and using high-throughput sequencing to quantify changes in relative abundance of individual mutants. The hypothesis is that, if the target of a drug or other genes in the same pathway are present in the library, such genes will display an excessive fitness defect due to the synergy between the dual stresses of protein depletion and antibiotic exposure. While assays at a single drug concentration are susceptible to noise and can yield false-positive interactions, improved detection can be achieved by requiring that the synergy between gene and drug be concentration-dependent. We present a novel statistical method based on Linear Mixed Models, called CGA-LMM, for analyzing C-G data. The approach is designed to capture the dependence of the abundance of each gene in the hypomorph library on increasing concentrations of drug through slope coefficients. To determine which genes represent candidate interactions, CGA-LMM uses a conservative population-based approach in which genes with negative slopes are considered significant only if they are outliers with respect to the rest of the population (assuming that most genes in the library do not interact with a given inhibitor). We applied the method to analyze 3 independent hypomorph libraries of M. tuberculosis for interactions with antibiotics with anti-tubercular activity, and we identify known target genes or expected interactions for 7 out of 9 drugs where relevant interacting genes are known.

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Some Limits Using Random Slope Models to Measure Academic Growth

Cited by 14 publications

References 20 publications

Association of Cognitive Function Trajectories in Centenarians With Postmortem Neuropathology, Physical Health, and Other Risk Factors for Cognitive Decline

Association of Cognitive Function Trajectories in Centenarians With Postmortem Neuropathology, Physical Health, and Other Risk Factors for Cognitive Decline

Subjective cognitive decline is a better marker for future cognitive decline in females than in males

An improved statistical method to identify chemical-genetic interactions by exploiting concentration-dependence

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