Inference in quantile analysis has received considerable attention in the recent years. Linear quantile mixed models (Geraci and Bottai 2014) represent a ?exible statistical tool to analyze data from ...sampling designs such as multilevel, spatial, panel or longitudinal, which induce some form of clustering. In this paper, I will show how to estimate conditional quantile functions with random e?ects using the R package lqmm. Modeling, estimation and inference are discussed in detail using a real data example. A thorough description of the optimization algorithms is also provided.
When using accelerometers to measure physical activity, researchers need to determine whether subjects have worn their device for a sufficient period to be included in analyses. We propose a minimum ...wear criterion using population-based accelerometer data, and explore the influence of gender and the purposeful inclusion of children with weekend data on reliability.
Accelerometer data obtained during the age seven sweep of the UK Millennium Cohort Study were analysed. Children were asked to wear an ActiGraph GT1M accelerometer for seven days. Reliability coefficients(r) of mean daily counts/minute were calculated using the Spearman-Brown formula based on the intraclass correlation coefficient. An r of 1.0 indicates that all the variation is between- rather than within-children and that measurement is 100% reliable. An r of 0.8 is often regarded as acceptable reliability. Analyses were repeated on data from children who met different minimum daily wear times (one to 10 hours) and wear days (one to seven days). Analyses were conducted for all children, separately for boys and girls, and separately for children with and without weekend data.
At least one hour of wear time data was obtained from 7,704 singletons. Reliability increased as the minimum number of days and the daily wear time increased. A high reliability (r = 0.86) and sample size (n = 6,528) was achieved when children with ≥ two days lasting ≥10 hours/day were included in analyses. Reliability coefficients were similar for both genders. Purposeful sampling of children with weekend data resulted in comparable reliabilities to those calculated independent of weekend wear.
Quality control procedures should be undertaken before analysing accelerometer data in large-scale studies. Using data from children with ≥ two days lasting ≥10 hours/day should provide reliable estimates of physical activity. It's unnecessary to include only children with accelerometer data collected during weekends in analyses.
Accelerometers are commonly used in human medical and public health research to measure physical movement, which is relevant in a wide range of studies, from physical activity and sleep behaviours ...studies, to identification of movement patterns in people affected by diseases of the locomotor system and prediction of risk of injury in high performance sports. The accelerometer output provides the intensity (activity count) and timing (timestamp) of the movement, which can be used to define bouts of activity (periods of sustained movement of a given intensity). In some contexts, it may be important to include both dimensions to obtain a broader and deeper understanding of the phenomenon under study. Such is the case of a large‐scale epidemiological investigation on the daily and weekly physical activity behaviours of school‐aged children enrolled in the UK Millennium Cohort Study, which has motivated the present article. I present a statistical approach to joint modelling of intensity and timing of activity bouts that takes advantage of the circular nature of the timing. The model, which accounts for the longitudinal structure of the observations, is remarkably simple to implement using standard statistical software.
Preliminary evaluations of behavioral interventions, referred to as pilot studies, predate the conduct of many large-scale efficacy/effectiveness trial. The ability of a pilot study to inform an ...efficacy/effectiveness trial relies on careful considerations in the design, delivery, and interpretation of the pilot results to avoid exaggerated early discoveries that may lead to subsequent failed efficacy/effectiveness trials. "Risk of generalizability biases (RGB)" in pilot studies may reduce the probability of replicating results in a larger efficacy/effectiveness trial. We aimed to generate an operational list of potential RGBs and to evaluate their impact in pairs of published pilot studies and larger, more well-powered trial on the topic of childhood obesity.
We conducted a systematic literature review to identify published pilot studies that had a published larger-scale trial of the same or similar intervention. Searches were updated and completed through December 31st, 2018. Eligible studies were behavioral interventions involving youth (≤18 yrs) on a topic related to childhood obesity (e.g., prevention/treatment, weight reduction, physical activity, diet, sleep, screen time/sedentary behavior). Extracted information included study characteristics and all outcomes. A list of 9 RGBs were defined and coded: intervention intensity bias, implementation support bias, delivery agent bias, target audience bias, duration bias, setting bias, measurement bias, directional conclusion bias, and outcome bias. Three reviewers independently coded for the presence of RGBs. Multi-level random effects meta-analyses were performed to investigate the association of the biases to study outcomes.
A total of 39 pilot and larger trial pairs were identified. The frequency of the biases varied: delivery agent bias (19/39 pairs), duration bias (15/39), implementation support bias (13/39), outcome bias (6/39), measurement bias (4/39), directional conclusion bias (3/39), target audience bias (3/39), intervention intensity bias (1/39), and setting bias (0/39). In meta-analyses, delivery agent, implementation support, duration, and measurement bias were associated with an attenuation of the effect size of - 0.325 (95CI - 0.556 to - 0.094), - 0.346 (- 0.640 to - 0.052), - 0.342 (- 0.498 to - 0.187), and - 0.360 (- 0.631 to - 0.089), respectively.
Pre-emptive avoidance of RGBs during the initial testing of an intervention may diminish the voltage drop between pilot and larger efficacy/effectiveness trials and enhance the odds of successful translation.
In regression applications, the presence of nonlinearity and correlation among observations offer computational challenges not only in traditional settings such as least squares regression, but also ...(and especially) when the objective function is nonsmooth as in the case of quantile regression. Methods are developed for the modelling and estimation of nonlinear conditional quantile functions when data are clustered within two-level nested designs. The proposed estimation algorithm is a blend of a smoothing algorithm for quantile regression and a second order Laplacian approximation for nonlinear mixed models. This optimization approach has the appealing advantage of reducing the original nonsmooth problem to an approximated L2 problem. While the estimation algorithm is iterative, the objective function to be optimized has a simple analytic form. The proposed methods are assessed through a simulation study and two applications, one in pharmacokinetics and one related to growth curve modelling in agriculture.
To estimate the risks of mortality and morbidities in large for gestational age (LGA) infants relative to appropriate for gestational age infants born at 22-29 weeks of gestation.
Data on 156 587 ...infants were collected between 2006 and 2014 in 852 US centers participating in the Vermont Oxford Network. We defined LGA as sex-specific birth weight above the 90th centile for gestational age measured in days. Generalized additive models with smoothing splines on gestational age by LGA status were fitted on mortality and morbidity outcomes to estimate adjusted relative risks and their 95% CIs.
Compared with appropriate for gestational age infants, being born LGA was associated with decreased risks of mortality, respiratory distress syndrome, patent ductus arteriosus, necrotizing enterocolitis, late-onset sepsis, severe retinopathy of prematurity, and chronic lung disease. Early onset sepsis and severe intraventricular hemorrhage were increased among LGA infants, but these risks were not homogeneous across the gestational age range.
Being born LGA was associated with lower risks for all the examined outcomes except for early onset sepsis and severe intraventricular hemorrhage.
Objective To describe levels of physical activity, sedentary time and adherence to Chief Medical Officers (CMO) physical activity guidelines among primary school-aged children across the UK using ...objective accelerometer-based measurements. Design Nationally representative prospective cohort study. Setting Children born across the UK, between 2000 and 2002. Participants 6497 7-year-old to 8-year-old singleton children for whom reliable accelerometer data were available for at least 10 h a day for at least 2 days. Main outcome measures Physical activity in counts per minute (cpm); time spent in sedentary and moderate-to-vigorous intensity physical activity (MVPA); proportion of children meeting CMO guidelines (≥60 min/day MVPA); average daily steps. Explanatory measures Gender, ethnicity, maternal current/most recent occupation, lone parenthood status, number of children in the household and country/region of residence. Results The median daily physical activity level was 595 cpm (IQR 507, 697). Children spent a median of 60 min (IQR 47–76) in MVPA/day and were sedentary for a median of 6.4 h/day (IQR 6–7). Only 51% met CMO guidelines, with girls (38%) less active than boys (63%). Children took an average of 10 229 (95% CI (8777 to 11 775)) steps each day. Children of Indian ethnicity were significantly less active overall than all other ethnic groups. Children of Bangladeshi origin and those living in Northern Ireland were least likely to meet CMO guidelines. Conclusions Only half of 7-year-old children in the UK achieve recommended levels of physical activity, with significant gender, ethnic and geographic variations. Longitudinal studies are needed to better understand the relevance of these (in)activity patterns for long-term health and well-being. In the meantime population-wide efforts to boost physical activity among young people are needed which are likely to require a broad range of policy interventions.
Temporal characterisation of physical activity in children is required for effective strategies to increase physical activity (PA). Evidence regarding determinants of physical activity in childhood ...and their time-dependent patterns remain inconclusive. We used functional data analysis (FDA) to model temporal profiles of daily activity, measured objectively using accelerometers, to identify diurnal and seasonal PA patterns in a nationally representative sample of primary school-aged UK children. We hypothesised that PA levels would be lower in girls than boys at play times and after school, higher in children participating in social forms of exercise (such as sport or play), and lower among those not walking to school.
Children participating in the UK-wide Millennium Cohort Study wore an Actigraph GT1M accelerometer for seven consecutive days during waking hours. We modelled 6,497 daily PA profiles from singleton children (3,176 boys; mean age: 7.5 years) by means of splines, and used functional analysis of variance to examine the cross-sectional relation of time and place of measurement, demographic and behavioural characteristics to smoothed PA profiles.
Diurnal and time-specific patterns of activity showed significant variation by sex, ethnicity, UK country and season of measurement; girls were markedly less active than boys during school break times than boys, and children of Indian ethnicity were significantly less active during school hours (9:30-12:00). Social activities such as sport clubs, playing with friends were associated with higher level of PA in afternoon (15:00-17:30) and early evenings (17:30-19:30). Lower PA levels between 8:30-9:30 and 17:30-19:30 were associated with mode of travel to and from school, and number of cars in regular use in the household.
Diminished PA in primary school aged children is temporally patterned and related to modifiable behavioural factors. FDA can be used to inform and evaluate public health policies to promote childhood PA.
Additive models are flexible regression tools that handle linear as well as non-linear terms. The latter are typically modelled via smoothing splines. Additive mixed models extend additive models to ...include random terms when the data are sampled according to cluster designs (e.g. longitudinal). These models find applications in the study of phenomena like growth, certain disease mechanisms and energy expenditure in humans, when repeated measurements are available. We propose a novel additive mixed model for quantile regression. Our methods are motivated by an application to physical activity based on a data set with more than half a million accelerometer measurements in children of the UK Millennium Cohort Study. In a simulation study, we assess the proposed methods against existing alternatives.
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